Method of generating raster data useful in reproducing multitone image

Abstract: A priority grade is provided to each of graphic figures (LP1-LP8). Respective contour lines of the graphic figures are classified into two groups according to respective locations thereof. Respective contour lines in the two groups are serially selected in a descent order of main scanning coordinate values, and are compared with each other to specify a cross point having a largest coordinate value within a selected pair of cross points. A component of the raster data is generated on the basis of the selected cross point when a priority grade of the selected cross point satisfies a predetermined condition in connection with respective priority grades of the other cross points.

Description: BACKGROUND OF THE INVENTION Field of the Invention The present invention relates to a method of generating a raster data on the basis of respective contour vectors of graphic figures in order to produce a multitone image containing the graphic figures through raster scan of an image plane for each scanning line, where the term "graphic figures" expresses character fonts, geometric figures and others which are representable on a plane. Description of the Prior Arts In the field of commercial printing and the like, techniques for automatically reproducing an image containing a plurality of graphic figures through raster scan have been developed. Such techniques are disclosed in EP-A-0 236 781 and WO 84/03967. In one of the techniques, a raster data for generating run-length codes is obtained by finding intercrossing points of scanning lines and the contours of the graphic figures and then sorting and merging the intercrossing points according to respective main scanning condinates thereof. However, the prior art can be only applied to binary images, and no techniques have been proposed for systematically generating a raster data in order to reproduce a multitone image. Therefore, when it is required to reproduce a multitone image through raster scan, an original image is produced through manual operation, and an image data for the raster scan of a photosensitive material is generated by reading the original image with a photoelectric image reader. Such a manual operation is laborious, and long time is required until desired raster data is obtained. SUMAMRY OF THE INVENTION The present invention is intended for a method of generating a raster data which is used for producing a multitone image having graphic figures through a raster scan of an imaging plane for each scanning line. According to the present invention, the method comprises the steps of: (A1) preparing sets of contour lines which express contours of the graphic figures, respectively, (A2) determining an imaging condition and a priority grade of each graphic figure for production of the multitone image, (A3) generating an attributive data expressing the imaging condition and the priority grade for each graphic figures, and (A4) relating the attributive data to each contour line belonging to the sets of contour lines for each graphic figure. In the next step (A5), the contour lines belonging to the sets of contour lines are classified into first and second groups according to respective locations of the contour lines in the contours, where the first group consists of first contour lines which face an upstream side of a main scanning in the raster scan, and the second group consists of second contour lines which face a downstream side of the main scanning. First cross points of the first contour lines and a scanning line are obtained in the step (A6). Generated for each first cross point in the step (A7) is a first cross point data which includes a main scanning coordinate value of the first cross point and the attributive data related to a contour line from which the first cross point belongs. Similarly, in the step (A8), second cross points of the second contour lines and the scanning line are obtained, and in the step (A9), generated for each second cross point is a second cross point data which includes a main scanning coordinate value of the second cross point and the attributive data related to a contour line to which the second cross point belongs. Respective main scanning coordinate values of the first cross points are compared with each other to serially extract a first object point from the first cross points along an order from the upstream side to the downstream side, in the step (A10). Similarly, respective main scanning coordinate values of the second cross points are compared with each other to serially extract a second object point from the second cross points along the order, in the step (A11). Then, in the step (A12), respective main scanning coordinate values of the first and second object points are compared with each other to specify a cross point which is located at a position nearer to the upstream side within the first and second object points. In the step (A13), one of conducting the following steps (A13a) and (A13b), is conducted. That is, (A13a) when a specified cross point which is specified on the step (A12) is the first object point, the attributive data of the first objects point is registered in a first memory and, (A13b) when the specified cross point is the second object point, an attributive data which is identical to the attributive data of the second object point is deleted from the first memory. The method further comprises the steps of (A14) detecting a change of a maximum priority grade within attributive data which are currently registered in the first memory where the change is caused by the step (A13), (A15) in response to the change of the maximum priority grade, finding an attributive data in the first memory to which a changed maximum priority grade belongs, (A16) generating a component of the raster data on the basis of the imaging condition belonging to the attributive data which is found in the step (A15) and the main scanning coordinate value of the specified cross point, (A17) repeating the steps (A11) through (A16) until all of the first and second cross points are extracted in the step (A11) to generate components of the raster data for the scanning line, and (A18) repeating the steps (A6) through (A17) for each of the scanning lines arrayed in a subscanning direction to generate the raster data. In the present invention, the term "multitone" indicates the condition where a plurality of imaging tones, e.g., halftone dot percentages in a halftone dot image, black/white levels in a binary image and other imaging levels which can be discriminated from each other, may be included in an image. In particular, the present invention is quite effective in a multitone image which has three or more tones. According to the present invention, overlapped graphic figures can be imaged at an arbitrary order in spatial priority since a priority grade is provided to each graphic figure. The attributive data including the priority grade is provided to the cross point data expressing respective cross points of the contour lines and each scanning line. A cross point having a higher priority is used for generating the raster data spatially prior to another cross point having a lower priority, and therefore, the graphic figures are overlapped in a desired order of spatial priority. Preferably, a combination of the steps (A6) and (A7) is conducted in parallel with a combination of the steps (A8) and (A9). In an aspect of the present invention, the step (A10) includes the steps of: (A101) sorting respective first cross point data for the first cross points according to respective main scanning coordinate values in the first cross point data to store sorted first cross point data in a second memory, and (A102) serially reading out the sorted first cross point data from the second memory in an order along the scanning line to serially provide the first object point. Similarly, the step (A11) includes the steps of: (A111) sorting respective second cross point data for the second cross points according to respective main scanning coordinate values in the second cross point data to store sorted second cross point data in a third memory, and (A112) serially reading out the sorted second cross point data from the third memory in the order along the scanning line to serially provide the second object point. A same priority grade may be commly assigned to two or more grades figures. Accordingly, an object of the present invention is to systematically generate a raster data which is used for producing a multitone image having plurality of graphic figures. Another object of the present invention is to generate a raster data at a high speed. These and other objects, features, aspects and advantages of the present invention will become more apparent from the following detailed description of the present invention when taken in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1A is a block diagram of a raster data generator operable to generate a raster data according to a preferred embodiment of the present invention, Fig. 1B is a block diagram showing vector processing parts 5a and 5b included in the raster data generator, Fig. 2 shows an example of a multitone image having a plurality of graphic images, Fig. 3 shows examples of data formats used in the preferred embodiments, Fig. 4 is an explanatory diagram showing contour vectors, Fig. 5 and Fig. 6 are explanatory diagrams which schematically show imaging priority grades, Fig. 7 is an explanatory diagram showing a criterion for classifying contour vectors into validation vectors and invalidation vectors, Fig. 8 is an explanatory diagram showing validation vectors and invalidation vectors in the character "A", Fig. 9 is a block diagram of a raster data generating part 100, Fig. 10 shows respective orders of validation cross points and invalidation cross points, Fig. 11 is an explanatory diagram showing a process of comparing Y-values with each other, Fig. 12 through Fig. 14 are flowchart showing a process of generating a raster data, Fig. 15 and Fig. 16 are diagrams showing processings of respective data in the preferred embodiment, and Fig. 17 through Fig. 19 are diagrams showing an example of a intra-layer processing. DESCRIPTION OF PREFERRED EMBODIMENTS A. Process of Generating Graphic Data Fig. 1A is a schematic block diagram showing a raster data generator according to a preferred embodiment of the present invention, where bus lines are expressed by single lines. The following description will be directed to an example for generating a raster data usable to reproduce a multitone image shown in Fig. 2 through raster scan of a photosensitive film. Slant lines, sand dots and other patterns filling the regions in Fig. 2 represent respective halftone dot percentages T in halftone dot recording as shown in the foot margin of Fig. 2. Furthermore, the symbols X and Y represent main scanning and subscanning coordinate axes, respectively. Referring to Fig. 1, the raster data generator 1 comprises a graphic input device 2 having a digitizer and others. Through input operation of the graphic input device 2, a graphic data D F having the data format of Fig. 3A is generated in the graphic input device 2 for each graphic figure. With respect to the character "A" shown in Fig. 2, for example, the graphic data D F has the following information: (a) The number N of contour lines (i.e., closed loops LP a and LP b shown in Fig. 4) forming the character "A", (b) Data VD a and VD b expressing respective positions and shapes of the closed loops LP a and LP b , and (c) Attributive data AS which expresses imaging attribution of the graphic figure "A". Within these data, the closed loop data VD a and VD b include a sequence of respective two-dimensional coordinates of the points Q a , Q b , ... Q i , Q j , ..., which are respective apexes of polygons expressing the closed loops LP a and LP b . The order in the sequence indicates the respective directions of contour vector which are so determined that the respective left sides and right sides of the contour vectors correspond to filling and unfilling regions, respectively, when the contour vectors are observed from the starts points to the end points thereof. This situation is understood more clearly, when Fig. 4 is compared with Fig. 2. In other word, contours whose inner region should be filled with colors or tints are expressed by a counter clockwise loop of vectors, while contours whose inner region should be unfilled are expressed by a clockwise loop of vectors. The attributive data AS has an imaging priority data P and an imaging condition data CD having multi-levels. The imaging condition data CD indicates an imaging condition under which the inner or outer region of the graphic figure is imaged or reproduced, and in the preferred embodiment, a halftone dot condition data or a halftone dot percentage T is included in the imaging condition data CD. The halftone dot condition data T may selectively indicate not only 0 % and 100 % but also other percentages between 0 % and 100 %, and therefore, the halftone dot condition data is a "multilevel data" for selecting one of halftone levels. For example, when it is desired to fill the character "A" shown in Fig. 2 with a tint of 20 %, the value of T = 20 % is designated in the imaging condition data CD. The imaging condition data CD may include information for designating a gradation rate, a color and other characteristics of the graphic image. The first broken part of Fig. 3A shows a possibility that such an additional information is included in the imaging condition data CD. On the other hand, the imaging priority data P indicate a spatial priority grade in which a corresponding graphic figure is imaged when the graphic figure is overlapped with another graphic figure is a multitone image. The reason why the priority grade is introduced into multitone imaging is as follows: Referring to Fig. 4 corresponding to Fig. 2, it is supposed that a figure group FG has eight graphic figures which are formed by closed loops LP1 through LP8, respectively. As will be understood by comparing Fig. 4 with Fig. 2, a desired image of Fig. 2 cannot be obtained if the image is reproduced under the rule where graphic figures are overlapped according to one of the ascent and descent orders in the respective halftone percentages thereof. For example, a grpahic figure having a larger halftone dot percentage should be imaged at a high priority in a region 21 of Fig. 2, while a graphic figure having a smaller halftone dot percentage should be imaged at a high priority in a region 22. Under the circumstances, the raster data generator 1 according to the preferred embodiment is so constructed that respective priority grades of graphic figures in image reproduction can be arbitrarily designated regardless of respective halftone dot percentages of the graphic figures, and imaging priority data P indicating the priority grade is given to the graphic data D F . The designation of the priority grades may be attained by assigning the priority numeral "1", "2", ..., "N TOT " to the graphic figures in one-to-one correspondence, where the integer N TOT indicates the total number of graphic figures. However, it is a rare case that all of the N TOT graphic figures overlap each other on a same region, and in practice, the number of graphic figures overlapping on a same region is relatively small even if the number N TOT is large. Therefore, it may be sufficient for image reproduction that the upper limit N LIM of the number of overlapping graphic figures is previously assumed, and all of the graphic figures are classified into N LIM groups according to relative priority grades or ranks of the graphic figures. In accordance with the latter principle, the upper limit N LIM is assumed to be "5" in the preferred embodiments, and each of the graphic figures LP1 through LP8 is provided with one of the priority grades "1" through "5", where the graphic figures LP1 through LP8 are defined as graphic figures which are formed by the closed loops LP1 through LP8, respectively. In other words, imaginary five priority layers LR1 through LR5 corresponding to the priority grades "1" through "5" are assumed as shown in Fig. 6, and each of the graphic figures LP1 through LP8 is assigned to one of the layers LR1 through LR5. When the priority grades "1" through "5" are so defined that a higher priority grade corresponds to a larger number, i.e., the highest priority grade is "5", the graphic figures shown in Fig. 6 are reproduced according to a spatial priority order from the top layer LR5 to the bottom layer LR1. As will be understood from Fig. 6, the priority grades can e assigned to the graphic figures LP1 through LP8 regardless of the halftone dot percentages of the graphic figures LP1 through LP8. For example, although the halftone dot percentage 20 % is designated for the graphic figures LP4 and LP5 as shown in Fig. 5, the graphic figures LP4 and LP5 have a priority grade being higher than that for the graphic figure LP3 to which a halftone dot percentage 50 % is designated. The highest priority gade is given to the graphic figure LP8 to which a halftone dot percentage 100 % is designated. In Fig. 6, the graphic figures having a same halftone dot percentage are assigned to a same layer, for convenience of explanation. However, a plurality of graphic figure having different halftone dot percentages may belong to a same layer. In such a case, the plurality of graphic figures belonging to a same layer are reproduced according to a predetermined rule, for example, that a graphic figure having a larger halftone dot percentage is reproduced at a higher priority than that of another graphic figure having a smaller halftone dot percentage within the same layer. An example of a process according to the rule will be described layer. One of the priority grade "1" through "5" are also assigned to the character "A" shown in Fig. 2 for designating relative priority between the character "A" and the other graphic figures LP1 through LP8, although it is not illustrated in Fig. 6. B. Expansion of Graphic Data and Classification Thereof The graphic data D F having the above-indicated components is transmitted to a vector expansion part 3 shown in Fig. 1 to be expanded into contour vectors. For example, the closed loop LP a (Fig. 4) which is included in the character "A" is expanded into vectors Each of vector data expressing these vectors is an "enriched vector data" which has not only respective two-dimensional coordinates of terminal points (a start point and an end point) of a corresponding vector but also the attributive data AS obtained from the original graphic data. The enriched vector data may be a vector data D V1 or D V2 shown in Fig. 3B which is provided for each vector. However, the enriched vector data in the preferred embodiment is constructed in the form of a data D V shown in Fig. 3B, which has a data format different from the data D V1 and D V2 . Such an improvement is introduced in connection with a classification process through which the enriched vector data are classified into two types. Details of the classification process are as follows: First, it is to be noted that the directon of each contour vector indicates whether the contour vector exists on the front edge or the rear edge of the graphic figure to which the contour vector belongs, where the front edge and the rear edge are defined in connection with the direction (-Y) of a main scanning for the image reproduction. In other words, edges facing the upstream side of the main scanning are front edges, while those facing the downstream side of the main scanning are rear edges. For example, the leftward contour vectors and are "front edge vectors" existing on the front edges of the graphic figure or the character "A", while the rightward contour vectors and are "rear edge vector" existing on the rear edges of the same. Therefore, the respective directions of the contour vectors are indexes of the contour vectors by which the front edge vectors and the rear edge vectors are discriminated from each other. Since a main scanning is carried out along the direction (-Y), the imaging condition for a graphic figure should be validated when the main scanning reaches a front edge vector while it should be invalidated when the main scanning reaches a rear edge vector. Accordingly, the two types of the contour vectors, i.e., the front edge vectors and the rear edge vectors, have opposite characters with respect to the main scanning, and it is prefered to individually process the two types of the contour vectors. Under the circumstances, the respective enriched vector data are classified into front edge vector data expressing the front edge vectors and rear edge vector data expressing the rear edge vectors, in the preferred embodiment. The two types of the contour vectors may be also discriminated from each other according to the criterion whether a region on which an imaging condition should be validated exists or does not exist just under the contour vector when the main scanning is progressed along the downward directon (-Y) as shown in Fig. 4 with a dotted line. Consequently, the front edge vectors and the rear edge vectors are hereinafter called as "validation vectors" and "invalidation vectors", respectively. Similarly, the front edge vector data and the rear edge rector data are called as "validation vector data" and "invalidation vector data", respectively. The classification of the enriched vector data into the validation vector data and the invalidation vector data is attained by detecting respective directions of the contour vectors. More particularly, when the main scanning direction (-Y) is in the downward direction in Fig. 7, it is detected whether each of the contour vectors is in a rightward vector RV having a component in the rightward direction or a leftward vector LV having a component in the leftward direction. A contour vector is an invalidation vector if the contour vector is a rightward vector RV, while it is a validation vector if it is a leftward vector. Although upward vectors UV and downward vectors DV may be also taken into consideration, they are ignored in the preferred embodiment, since a graphic figure can be reproduced as long as the leftward vectors LV and the rightward vectors RV are provided. Through the classification process, the respective contour vectors forming the character "A" shown in Fig. 4, for example, are classified into validation vectors illustrated as black vectors shown in Fig. 8 and invalidation vectors illustrated as white vectors. As will be understood from the example shown in Fig. 8, a number of validation vectors often forms a chain thereof, and similarly, a chain of invalidation vectors is often found in a graphic figure. Consequently, contour vectors are traced along each of the closed loops LP a and LP b . The validation vectors and the invalidation vectors forming respective chains are collected for each chain, whereby respective data expressing the chains are generated. The enriched vector data D V shown in Fig. 3B is an example which is obtained through the above-indicated process, and the same is a validation vector data expressing a chain of the validation vectors shown in Fig. 8. The classification process is conducted in a vector classification part 4 shown in Fig. 1A in parallel with the expression process in the vector expansion part 3. C. Expansion into Cross Point Data Within the respective enriched vector data, the validation vector data and the invalidation vector data are transmitted to a validation vector processing part 5a and an invalidation vector processing part 5b, respectively. As shown in Fig. 1B, the validation vector processing part 5a has memories 7a and 8a which are alternately selected for read/write operations through a pair of bus switches 6a and 9a. The validation vector data are stored in a validation vector memory 10a through the paired buffer memories 7a and 8a. A validation point expansion part 11a reads out the validation vector data from the memory 10a to expand the validation vectors into cross points of the validation vectors and each scanning line. The expansion into the cross points may be carried out according to the technique disclosed in European Patent Publication No. EP-A2-0,200,885. An example of the cross point data expressing each cross point is shown in Fig. 3C, where the cross point data D C has the main scanning coordinate value Y of the corresponding cross point (CP in Fig. 4, for example) and the attributive data AS obtained from the corresponding enriched vector data. Since the cross point data D C is generated on each scanning line having a known subscanning coordinate value, the subscanning condinate value of the cross point may be omitted from the cross point data D C . The cross point data which is obtained from a validation vector data expresses a cross point of a scanning line and a front edge of the corresponding graphic figure, and therefore, the cross point data may be called as "a front point data" or "a validation point data" expressing "a validation cross point". The invalidation vector processing part 5a further comprises memories 13a and 14a, which are alternately selected for read/write operations through a pair of bus switches 12a and 15a. The respective validation point data for the validation cross points are stored in one of the memories 13a and 14a which is selected for each scanning line, and then, the respective validation point data are read out from the same to be delivered to a raster data generating part 100 (Fig. 1A) as a data D CA . An invalidation vector processing part 5b has a structure similar to the validation vector processing part 5a, and the correspondence between them is indicated by replacing the suffix "a" of the reference numerals with "b". The invalidation vector processing part 5a expands the invalidation vector data into "invalidation point data" or "rear point data" D CB , which expresses cross point ("invalidation cross points") of rear edge vectors and scanning lines, to deliver the data D CB to the raster data generating part 100 for each scanning line. The "scanning lines" in the operation of the raster data generator 1 correspond to scanning lines defined in a scan of a photosensitive material for image reproduction, which will be described later, and the data processing in the raster data generator 1 is conducted for each scanning line. The control of the raster data generator 1 is attained by means of a control part (not shown) operable to generate control signals synchronously with the scanning in the image reproduction. Since the respective data processings in the vector processing parts 5a and 5b are pipe-line processings in which the respective enriched vector data D Y are serially processed and expanded into the cross point data D CA (D CB ) to be serially delivered to the raster data generating part 100, the efficiency of the data processing in the raster data generator 1 is improved as compared with the case where the respective enriched vector data for many vectors are converted into the cross point data through a batch processing. Furthermore, since respective expansions of the validation vectors and the invalidation vectors are performed in parallel, the total speed in the expansion processing is further increased. D. Process of Sorting Cross Point Data Fig. 9 is a black diagram showing the internal structure of the raster data generator 100. The validation point data D CA and the invalidation point data D CB are delivered to a validation point sorting part 101a and an invalidation point sorting part 101b, respectively. The validation point sorting part 101a is operable to sort or permute the validation point data D CA for each scanning line according to their respective main scanning coordinate values, which will be also called as "Y-values", to thereby generate a data chain for each scanning line in which the validation point data are arranged in a descent order of the respective Y-values. Similarly, the invalidation point sorting part 101b is operable to sort or permute the invalidation point data D CB for each scanning line according to their respective Y-values, to thereby generate another data chain for each scanning line in which the invalidation point data are arranged in a descent order of the respective Y-values. Fig. 10 is an explanatory diagram showing the sorting process for the graphic figure group FG shown in Fig. 4. Validation points P 1s through P 8s and invalidation points P 1e through P 8e exist on the scanning line ℓ, and they have Y-values Y 1s through Y 8s and Y 1e through Y 8e , respectively. In Fig. 10, the respective ones of the validation points P 1s through P 8s are coupled with their corresponding ones of the invalidation points P 1s through P 8s by dotted lines in order to clarify the situation that the coupled two points (P 1s and P 1e ), for example) are obtained from a same graphic figure (LP1). Since the respective Y-values satisfy the inequalities: Y 1s > Y 4s > ... > Y 5e (1) Y 4e > Y 1e > ... > Y 2e (2) the validation point data for the validation cross points P 1s through P 8s and the invalidation point data for the invalidation cross points P 1e through P 8e are sorted into the orders of (3) and (4), respectively. P 1s , P 4s , ..., P 5s (3) P 4e , P 1e , ..., P 2e (4) The sorting process for the validation cross points and that for the invalidation cross points are performed in parallel, whereby the total speed of the sorting processes is increased. When the respective halftone dot conditions or percentages for the graphic figures LP1 through LP8 shown in Fig. 4 are expressed as T₁ through T₈, the halftone dot percentages T₁ through T₈ are related to the values in the range from 0 % to 100% as shown in Fig. 5. The respective priority grades of the graphic figures LP1 through LP8 are indicated in Fig. 6. Therefore, when the respective imaging priority data expressing the priority numerals "1" through "5" are represented by the symbols P₁ through P₅, respectively, the imaging priority data which is given to the graphic figure LP3, for example, is "P₂" according to the relationships shown in Fig. 5 and Fig. 6. Consequently, the imaging priority data P₂ and the halftone dot percentage T₃ associate with each of the crossing points P 3s and P 3e (Fig. 10) which are obtained from the graphic figure LP3. Similarly, each of the other graphic figures is associated with an imaging priority data and a halftone dot percentage. In accordance with the sorting of the validation cross points P 1s through P 8s , the respective validation point data are sorted or permuted, to be stored in a storage area 102a prepared for the sorted validation points. Similarly, the respective invalidation point data are sorted or permuted in accordance with the sorting of the invalidation cross points P 1e through P 8e , and are stored in another storage area 102b prepared for the sorted invalidation points. Fig. 11 shows the state where the validation cross point data and the invalidation cross point data are stored in these storage areas 102a and 102b according to the orders of (3) of (4), respectively. Since each of the cross point data has the corresponding attributive data which is succeeded from the enriched vector data, the cross point data may be called as "enriched cross point data". In the preferred embodiment, functional blocks which are included in a block 110 are realized by a software, i.e., a programmed computer. Therefore, the storage areas 102a, 102b and 105-107 correspond to storage areas in a memory (not shown) provided in the computer, and a Y-values comparing means 103 and a data processing means 104, which will be described later, are functional means embodied by a CPU and a program in the computer. E. Process of Generating Raster Data (F-1) Summary of the Process Then, the validation point data D CA and the invalidation point data D CB are combined with each other to generate a raster data which is used for reproducting the graphic figures through raster scanning. In this process, the cross point data D CA and D CB are referred to in a descent order of respective Y-values included therein, and the raster data is generated according to an imaging condition associated with a graphic figure having the highest priority grade within respective priority grades included in the cross point data which are being referred to and have not been used for generating the raster data yet. (F-2) Structure and Illustration Forms in the Drawings In order to perform the process, which will be described later with reference to Fig. 12 through Fig. 14, the raster data generating point 100 (Fig. 9) is provided with a stack area 105, a counter area 106, a register 108 and a resulting data storage area 107. Within those areas, the stack area 105 serves as a storage area in which the attributive data are registered according to a rule described later. The number of the attributive data which are registered in the stack area 105 are counted for each of the priority grades "1" through "5" by means of the counter are 106. A data in the register 108 indicates a priority grade belonging to the attributive data which was used for having generated a component of the resulting data or raster data which was generated latest within components having been obtained. Fig. 15 shows the contents of these areas at each process stage t . In Fig. 15, symbol "RG" indicate the register 108, and another symbol "P MAX " indicates a priority grade which is currently registered in the register 108. The reason why the suffix "MAX" exists in the symbol "P MAX " is that the resulting data is generated using an attributive data which has a maximum priority grade within attributive data currently registered in the stack area 105. The priority grade P MAX will be called as "a maximum priority grade". Furthermore, the respecive columns in Fig. 15 which are indicated in the section of "counter 106" with the priority grade P₁ through P₅ show how many cross point data having each priority grade are currently registered in the stack area 105. A registered total number M indicates the total number of the attributive data which are currently registered in the stack area 105. A data D which is obtained as the resulting data is the raster data which are used for generating a run-length data, and the same is stored in the resulting date storage area 107 in Fig. 9. The respective process stages t = t₀ , t₁, ..., t₁₆ in Fig. 15 correspond to respective stages or timings in the process of generating the raster data, and from a spatial point of view, they are process stages serially appearing as a scan of the sorted cross point data progresses along a scanning line in the directon (-Y). Further, Fig. 16 is provided in order to show the attributive data which are registered in the stack area 105 at respective time points or stages for each of the priority grades P₁ through P₅, where the reference symbols SP and EP indicate a starting time and an ending time of a main scanning, respectively. White fat arrows in Fig. 16 show periods in which the resulting raster data are obtained from corresponding attributive data. Dotted arrows indicate when the attributive data other than those used for generating components of the resulting raster data are registered in or deleted form the stack area 105. (F-3) Data comparison for Registration Details of the process using the above-indicated structure are as follows. First, the stack area 105, the counter area 106 and others are cleared, whereby the raster data generator 100 is initialized (the process step S1 in Fig. 12A). In the next process step S2, a maximum Y-value is extracted from the Y-values in the validation point data which are being stored in the validation point storage area 102a and have not been processed for generating the raster data. When the extracted maximum Y-value is written as "Y A ", the maximum Y-value Y A at this time is Y 1s as understood from Fig. 11. Similarly, a maximum value is extracted form the Y-values in the invalidation point data which are being stored in the invalidation point storage area 102b and have not been used for generating the raster data, the extracted maximum Y-value being written as "Y B ". In the example of Fig. 11, the maximum Y-value at this time is Y 4e . A Y-value comparing means 103 in Fig. 9 compares the maximum Y-values Y A and Y B with each other in the process step S3. When the condition Y A > Y B is satisfied, i.e., when the maximum Y-value Y A in the validation cross points is larger than the maximum Y-value Y B in the invalidation cross points, the process is forwarded to the process step S300. The process step S300 is provided in order to detect the state where a same halftone dot percentage or "T-value" is being registered in the resulting data storing area 107 two times in succession, and to delete one of them. Details of the process step S300 are shown in Fig. 12B, and the process step S300 is meaningful when the following process steps S100 and/or S200 are repeated two or more times. After passing through the process step S300, a data processing is performed in the process step S100 on the basis of a validation point data (Y i , T j , P k ) to which the extracted maximum Y-value (a prior coordinate value) Y A belongs. In the example shown in Fig. 11, the cross point data for the validation cross point P 1s is employed in the process step S100 at the first execution thereof, i.e., (Y i , T j , P k ) = (Y 1s , T₁, P₁) Details of the process step S100, are shown in Fig. 13, in which the maximum priority grade P MAX is compared with the value P k (the process step S101). In the case where an initial value of the maximum priority grade P MAX is set at (-1) and the respective data value of the priority grade P₁ through P₅ are "1" through "5", respectively, the condition P MAX < P k is always satisfied with respect to a cross point which is extracted first. Consequently, the process is forwarded to the next process step S102, in which the value of the maximum priority grade P MAX is forced into the value of P k . With respect to the validation point P 1s in Fig. 11, for example, the value P k is P₁ and the maximum priority grade P MAX becomes P MAX = P₁ (=1). This is also indicated in the row of t = t₁ in Fig. 15. Next, the Y-value Y N being included in the raster data which was brought into the resulting data storage area 107 latest up to the current time is extracted from the data D being registered in the area 107, and the Y-value Y N is compared with the Y-value Y i being processed (the process step S103). If Y i = Y N , i.e., the cross point being processed has the same Y-value with the newest component having been brought into resulting data and the priority grade of the former is higher than that of the latter due to the branching condition at the process step S101, the values Y N and T N in the newest resulting data are forced into the values T i and T j in the process step S104, respectively. If the Y i = Y N is not satisfied, the values Y i and T j are stored in the resulting data storage area 107 (the process step S105). Then, the attributive data T j and P k are registered in the stack area 105 (the process step S107), and the value in a P k -counter within the counter area 106 is incremented by (+1) in the process step S108. With respect to the validation cross point P 1s in Fig. 11, for example, the values of Y 1s and T₁ are stored in the resulting data storage area 107 since Y₁ ≠ Y₀ , under the condition that a Y-value Y₀ and a halftone dot percentage T₀ = 0% for the starting point SP of a main scanning are previously stored in the storage area 107. As long as there remain one or more cross points which have been processed yet, the process returns to the process steps S2 through the process step S4 after the execution of the process step S100. Therefore, when the above-indicated process is applied to the data shown in Fig. 11, the process is embodied as follows: In the first execution of the process, a comparing step 51 shown in Fig. 11 is conducted and the attributive data T₁ and P₁ for the validation cross point P 1s are registered in the stack area 105, as has been described above, whereby the data Y 1s and T₁ are obtained as the first component of the resulting data. In the second execution of the process, a next comparing step 52 shown in Fig. 11 is conducted. Since the condition Y 4s > Y 4e is satisfied as understood from Fig. 10, the data for the validation cross point P 4s are registered in the areas 105 and 107 (see the row of t = t₂ in Fig. 15). Since the maximum priority grade P MAX is forced into P₁ (=1) at the stage t = t₁ and the priority grade P₃ = (-3) of the validation cross point is higher than the current maximum priority grade P MAX , the data Y 4s and T₄ for the validation cross point P 4s are also stored in the resulting data storage area 107. In the third execution, a comparing step 53 in Fig. 11 is conducted. Similarly to the first and second executions, the data for the validation cross point P 3s rather than that for the invalidation cross point P 4e is employed, since the Y-value Y 3s of the point P 3S is larger than the Y-value Y 3e of the point P 3e . However, the priority grade of the validation cross point is P₂ (=2), and it is lower than the maximum priority grade P MAX which was updated when the newest resulting data Y 4s and T₄ were generated. Accordingly, the process jumps from the process step S101 to the process step S107. In order words, although the attributive data T₃ and P₂ are additionaly stored in the stack area 105, the same is not reflected to the resulting data D at this time. In summary, during the validation cross points are successively extracted and registered, the respective attributive data for the validation cross points are added to the resulting data only if the respective priority grades of the extracted validation cross points are higher than the current maximum of the respective priority grades in the attributive data being registered in the stack area 105. This character of the process will be also understood from the white fat arrows which are indicated in the period from t = t₁ to t = t₄ (or the period of Y 1s ≦ Y ≦ Y 6s ) in Fig. 16. The process step S106 is provided for processing the attributive data in the case where neighboring two or more cross points exist on a same priority layer (Fig. 6), and it will be described later as an "intra-layer processing". (E-4) Data Comparison for Deletion After the comparing step 54 in Fig. 11 is conducted to register the attributive data of the validation cross point P 6s , the respective Y-values of the validation cross point P 8s and the invalidation cross point P 4e are compared with each other according to the comparing step 55. As seen in Fig. 10, the respective Y-values Y 8s and Y 4e satisfy the condition Y 8s < Y 4e . Consequently, the process is forwarded from the process step S3 to the process step S200 in Fig. 12A through the process step S300, whereby a data processing is performed on the basis of the invalidation point data (Y 4e , T₄, P₃) for the invalidation cross point P 4e . Details of the process step S200 are shown in Fig. 14A and Fig. 14B. In the process step S201, decremented by (+1) is the P k -counter included in the counter area 106, which is the P₃-counter in the current stage, whereby it is indicated that the number of the attributive data having the priority grade P₃ within those being currently registered in the stack area 105. In the next process step S202, the attributive data being identical to the attributive data T₄ and P₃ of the invalidation cross point P 4e are deleted from the stack area 105. Through the process step S202, the attributive data T₄ and P₃ which have been registered in the stack area 105 from the process stage t₂ in Fig. 15 are deleted from the area 105 at the process stage t₅. In other words, the attributive data of the validation cross point P 4s are conserved in the stack area 105 until the process reaches the invalidation cross point P 4e which is obtained for the same graphic figure with the validation cross point P 4s , and when it reaches the invalidation cross point P 4e , the attributive data are deleted from the area 105. The cross mark "x" in the Fig. 15 shows a deletion of a data from the stack area 105. In the next process step S203, the priority grade P k which is included in the attributive data having been deleted in the process step S202 is compared with the maximum priority grade P MAX being stored in the register 108. For the comparing step, the value of the priority grade P k has been memorized so that it can be referred to even after it is deleted from the area 105. The maximum priority grade P MAX is "4" until the process reaches the process stage t₅ in Fig. 15, and the current maximum priority grade P MAX is higher than the deleted priority grade P₃. Therefore, it is recognized that another attributive data having a priority grade higher than P₂ remains in the stack area 105 after the attributive data having the priority grade data P₃ is deleted. According to the rule where the raster data is generated on the basis of the attributive data having a maximum priority grade within those being stored in the stack area 105, the invalidation cross point P 4e is not employed as a raster boundary point, since an attributive data having the previous maximum priority grade remains in the stack area 105 even after the priority grade data P₃ is deleted. Accordingly, when the condition P k < P MAX is confirmed in the process step S203 in Fig. 14, the process using the invalidation cross point P 4e is completed without passing through the process steps S204 through S206. Then the comparing step 56 in Fig. 11 is conducted, whereby the maximum Y-values Y 8s within the validation point data having not been processed is detected to be compared with the maximum Y-value Y 1e in the invalidation point data having not been processed. Since the condition Y 8s > Y 1e is satisfied as seen from Fig. 10, the process using the attributive data of the validation cross point P 8s is conducted according to the routine shown in Fig. 12A. Suppose that the above-indicated process is repeated whereby the process reaches the invalidation cross point P 8e . At this stage, it is found that the priority grade P₅ (=5) is included in the attributive data T₈ and P₅ which is to be deleted, and the priority grade P₅ is identical to the maximum priority grade P MAX (=P₅) at the time point just before the process reaches the process stage t₉ in Fig. 15. Therefore, the attributive data T₈ and P₅ are those having the maximum priority, and there is possibility that the value of the maximum priority grade is changed if the attributive data T₈ and P₅ are deleted from the stack area 105. Accordingly, when it is found in the process step S203 that P k = P MAX , the process is forwarded to the process step S210 (Fig. 14B) to judge whether or not the value in the P k -counter is "0" (the process step S211). If the value in the P k -counter is "0", it is recognized that the attributive data having the previous maximum priority grade P MAX (=P k ) does not remain in the stack area 105. Then, it is further judged whether or not there is a counter P m having a positive value within the counters P₁ through P k-1 whose respective priority grades are lower than the priority grade P k (the process step S212). If such a counter P m is found, it is recognized that one or more attributive data having respective priority grades lower than the priority grade P k are remaining in the stack area 105. In this case, the priority grade P m is regarded as a priority grade P k of an attributive data which is to be subjected to the following process (the process step S215). If there are two or more values of P m satisfying the condition m < k, the maximum value within them is employed as a new value of P k . For example, when the attributive data T₈ and P₅ which are identical to those of the invalidation point P 8e are deleted from the stack area 105 in the process stage t = t₉ in Fig. 15, the priority grade P₂ is found as the priority grade P m . Consequently, the priority grade P₂ is employed as the new priority grade P k in this case. In the next process step S216, an attribute data which has the same priority grade with the new value of P k and a halftone dot percentage (thereinafter called as a "T-value") having a maximum priority grade is extracted form the attribute data being stored in the stack area 105. The extracted attributive data are hereinafter written as (T z , P k ), where the T-value T z is that having the maximum priority grade within the stack area 105. A priority rule of T-values within each priority layer (an intra-layer priority rule) is previously determined, and it may be common to the respective priority layers, or alternately, different rules may be prepared for the priority layers. The intra-layer priority rule may be the rule where a larger T-value is prior to a smaller T-value. In the example at t = t₉ in Fig. 15, the extracted attributive data are T z = T₃ and P k = P₂ , since there is only one attribute data having the priority grade P₂. Then, in the process step S217, the value of the maximum priority grade P MAX is re-defined by the value of P k (=P₂). On the other hand, when a counter which has a positive value is not found in the process step S212, it is recognized that no attributive data are remaining on the stack area 105, and therefore, the value of the maximum priority grade P MAX is initialized again into (-1) in the process step S213, and the value of T z is set at 0 % in the process step S214. The process steps S204 through S206 correspond to the process steps S103 through S105 in Fig. 13, respectively. Accordingly, the newest component of the resulting data D is rewritten, or alternatively, next Y-value and T-value are added to the resulting data in the resulting data storage area 107 through the process steps S204 to S206, where the attributive data which are used in the process steps S205 and S206 are Y i and T z . The deletion process will be now described from another point of view with reference to Fig. 16. In the process stage t = t₉ , the invalidation cross point Y 8e is subjected to the current process, and the attributive data of the validation cross point Y 8e which is obtained from a same graphic figure LP8 with the invalidation cross point Y 8e are deleted from the stack area 105. Just after the deletion, extracted is the attributive data of the validation cross point Y 3s which has a maximum priority grade within the attributive data remaining in the stack area 105. Then, on the basis of the extracted attributive data of the validation cross point Y 3s , the newest raster condition in the resulting data D changes form T = T₈ to T = T₃ . The attributive data of the validation cross point is not reflected to the resulting data D at the process stage t = t₃ where the same is registered in the stack area 105. However, after all of the attributive data having a priority grade higher than the priority grade P₂ of the validation cross point Y 3s are deleted from the stack area 105, the priority grade P₂ is a maximum priority grade within the priority grades being registered in the stack area 105. consequently, the attributive data having the priority grade P₂ is employed for generating a new component of the resulting data D. That is, since an attributive data which is hidden behind other attributive data having higher priority grades in early stages is conserved in the stack are 105, the same contributes toward generating a component of the raster data in a later stage after the attributive data having higher priority grades are deleted. By repeating the above-indicated process, respective attributive data are serially registered in and deleted from the stack area 105 while storing respective components of the resulting data D in the resulting data storage area 102, as shown in Fig. 15 and Fig. 16. The step of registering the attributive data T₂ and P₁ at the process stage t = t₁₀ and that of generating the attributive data T₇ and P₄ may be performed in an arbitrary order thereof, since respective T-value Y 2s and Y 7s corresponding them are identical with each other (i.e., Y 2s = Y 7s ). This is the reason why the condition t₁₀ = t₁₁ is indicated in Fig. 16. As will be understood from Fig. 10, no validation cross point is additionally registered in the stack area 105 after the validation cross point Y 5s is registered, and the process stages following the same are directed to the deletion of the invalidation cross points. That is, there is no cross point in the validation point storage area 102a which remains being not subjected to the process of registering the attribute data, after the comparing step 57 in Fig. 11 is completed. In this case, the contents of the process step S2 in Fig. 12 are interpreted as "extract one of the remaining cross points in the invalidation point storage area 102b according to a descent order of Y-values". In summary, a new component is generated to be added to the resulting data D every time the maximum priority grade within the attributive data being currently registered in the stack area 105 is changed in response to the operation in which an attributive data is newly registered in or is deleted from the stack area 105. When all of the cross point data have been registered in and then deleted from the stack area 105, the process of generating the raster data for the current scanning line is completed and the process is forwarded to the next scanning line. (E-5) Intra-layer Processing In the example shown in Fig. 15 and Fig. 16, two or more cross points having a same priority grade do not neighbor each other on a scanning line. However, as shown in Fig.17, sometimes caused is the situation where a plurality of graphic figures LPA and LPB having a same priority grade P₂, for example, overlap each other, and Y-values Y as , Y bs , Y ae and Y be having the same priority grade P₃ neighbor each other on a same scanning line ℓ. Also in such a case, each of the Y-values Y as and Y bs for the validation cross points and each of the Y-values Y ae and Y be for the invalidation cross points are serially extracted from the respective sets of the Y-values according to descent orders of the Y-values, and the extracted Y-values are compared with each other (the comparing steps 61 and 62 shown in Fig. 18). Though the comparison, the larger one is detected to be subjected to the raster data generating process (the process step S2 in Fig. 12). When the extracted Y-value of a validation cross point is larger than that of an invalidation cross point, the process is forwarded to the process steps S100 in Fig. 13. If the extracted Y-value for the validation cross point is Y bs in Fig. 17, the result of the judgement in the process step S101 is " P k = P MAX " as shown in the row t = t₂ in Fig. 19. Then, the T-value T b of the validation cross point which shall be newly registered in the resulting data storage area 107 is compared with a T-value T a of a validation cross point which has been registered in the resulting data storage area 107 in the process step S106. If the intra-layer priority rule is so determined that a graphic figure having a larger halftone dot percentage is prior to that having a smaller halftone dot percentage in a same priority layer, a correction of the resulting data D or an addition of a component to the resulting data D is performed in the process steps S103 through S105 only when the condition T a < T b is satisfied Fig. 19 shows an example in which the condition T a < T b is satisfied, whereby the data Y bs and T b are added to the resulting data D as a new component thereof. In the process of deleting an attributive data from the stack area 105 in the case where a plurality of graphic figures overlap each other in a same priority layer, the result of the judgement in the process step S211 of Fig. 14B is "NO". In fact, even if the attributive data T a and P₃ are deleted in the process stage t = t₃ of Fig. 19, the value in the P₃-counter is "1" rather than "0". Consequently, the process steps S212 and S213 are bypassed, and the data T z and P k are forced into the remaining attributive data T b and P₃ in the same priority layer, whereby the maximum priority grade P MAX remains at P₃. In the process stage t = t₃ , the data Y ae and T b are stored into the resulting data storage area 107 through the process steps S204 and S206, and then, the data Y ae and T b are deleted in the process steps S300 in Fig. 12A. As a result, components which are unnecessary for the raster data is deleted, whereby an amount of data in the resulting data storage area 107 is decreased. Through the deletion of the data Y ae and T b , the halftone dot percentage T b is substantially valid in the image reproduction unitl the main scanning reaches the Y-values Y ae which is included in the component (Y ae , T b ) in the resulting data which generated in the process stage t = t₄ . Therefore, the resulting data or the raster data indicates that the inner region of the graphic figure LPB shown in Fig. 17 is to be filled with a tint having the halftone dot percentage T b at a higher priority than that of the other graphic figure T a . F. Process of Generating Run-length and Data Output The above-indicated process is conducted under the control with a process controlling means 104 shown in Fig. 9. When the process for a scanning line is completed, obtained is the state where the data D shown in column "result D" in Fig. 15 is being stored in the resulting data storage area 107. If the intra-layer process is also performed, the resulting data in the storage area 107 contains the data which is shown in the column "result D" in Fig. 19. Through repetition of the process of generating raster data for all of the scanning lines arrayed in the subscanning direction, the desired raster data for respective regions on an imaging plane are obtained. The resulting data D is transmitted to a run-length data generating part 16 in Fig. 1 as the raster data for each scanning line. The run-length data generating part 16 generates a run-length data D R (Fig. 3D) from respective component pairs of the data D each of which consists of two components whose respective Y-values neighbor each other in the direction (-Y). In the period between the two points which are indicated with the resulting data Y 6s T₆ and Y 8s T₈, respectively, for example, a component of the run-length data indicating a run-length RL = Y 6s - Y 8s and a halftone dot percentage T₆ is generated. Since the spatial priority order of the graphic figures has been taken into consideration in the process of generating respective components of the raster data D, the raster data D may have only T-values and Y-values i.e., the imaging condition data CD, and it is unnecessary to give a priority grade data P to the run-length data D R . The run-length data D R thus obtained for each scanning line is stored in a run-length memory 17 shown in Fig. 1. After the run-length data D R for all scanning lines are stored in the run-length memory 17, the data D R are transferred to a halftone dot recorder 3a. A recording drum 31 around which a photosensitive film 32 is wound is rotated in a direction ϑ for a main scanning, and a recording head 33 is moved in a direction X synchronously with the rotation of the recording drum 31 for a subscanning. An acoustic optical modulator which is provided in the recording head 3 is controlled according to the run-length data D R , whereby a laser beam from the recording head 33 is modulated. The photosensitive film 32 is exposed to the modulated laser beam for each scanning line, and the image shown in Fig. 2 is reproduced on the photosensitive film 32 as a latent halftone dot image through a raster scan thereof. As is understood by comparing a produced image for one scanning line which is shown in the right side of Fig. 16 with a timing chart in the data processings which is shown in the center part of Fig. 16, graphic figures having higher priority grades are recorded spatially prior to those having lower priority grades. Therefore, the raster data generator according to the present invention is suitable for the production of a multitone image. G. Modifications In the preferred embodiment described above, the validation cross points and the invalidation cross points are serially processed in a descent order of their respective Y-values, since the main scanning coordinate axis Y is defined in antiparallel to the main scanning direction (-Y). However, if the main scanning coordinate axis is defined in parallel to the direction Y, the cross points are serially processed in an ascent of their Y-values. The multitone imaging condition may include the halftone dot percentage, a density value, gradation, a color and/or other. Although it is preferred that the expansion of the validation vectors into validation cross points and the sorting thereof are conducted in parallel with those for invalidation vectors, they may be conducted in series. The intra-layer processing and the inter-layer processing may be performed independently, and in such a case, the enriched cross point data are subjected to the intra-layer processing before the inter-layer processing, for example. The respective contours of graphic figures may be expressed by segments having no directionality rather than vectors. "Front edge segments" and "rear edge segments" can be identified by adding flags for discriminating between them to segment data expressing the segments. In order to understand the character of the present invention more clearly, supposed is the technique where respective graphic figures on the priority layers LR1 through LR5 in Fig. 6 are serially overlapped one by one. Although a raster data can be also obtained through the technique, the process of serially overlapped the graphic figures becomes complicated. On the other hand, according to the present invention, all of the graphic figures in the respective priority layers can be processed and overlapped with each other through a single processing sequence, and therefore, it will be understood that the present invention is superior to the above-indicated technique. In the present invention, since graphic figures are expanded into cross points of the contours thereof and each scanning line, and a raster data is generated according to the priority grades which are transferred from the graphic figures to the cross points, the graphic figures are systematically reproduced under multitone imaging conditions. The efficiency and the speed in generating the raster data are increased because the cross points are classified into two groupes and respective cross points which are sorted in the two groups are serially compared with each other. In particular, the parallel processing of the two groups is effective for further increasing the speed in generating the raster data.

Claims: A method of generating raster data which is used for producing a multitone image having graphic figures (LP) through a raster scan of an imaging plane for each scanning line (1), characterised in that said method comprises the steps of: (A1) preparing sets of contour lines (QxQy) which express contours of said graphic figures (LP); (A2) determining an imaging condition (CD) and a priority grade (P k ) of each graphic figure (LP) for production of said multitone image; (A3) generating attributive data (AS) expressing said imaging condition (CD) and said priority grade (P k ) for each graphic figure (LP); (A4) relating said attributive data (AS) to each contour line (QxQy) belonging to said sets of contour lines for each graphic figure (LP); (A5) classifying contour lines (QxQy) belonging to said sets of contour lines into first and second groups according to respective locations of said contour lines (QxQy) in said contours, where said first group consists of first contour lines (QxQy) which are directed towards the upstream side of a main scanning direction (+y) of said raster scan, and said second group consists of second contour lines (QxQy) which are directed towards the downstream side of said main scanning direction (-y); (A6) obtaining first cross points (CP A ) of said first contour lines and a scanning line (1); (A7) for each first cross point (CP A ), generating first cross point data (D CA ) which includes a main scanning coordinate value of the first cross point (CP A ) and said attributive data (AS) related to the contour line from which the first cross point (CP A ) is obtained; (A8) obtaining second cross points (CP B ) of said second contour lines and said scanning line (1); (A9) for each second cross point (CP B ), generating second cross point data (D CB ) which includes a main scanning coordinate value of the second cross point (CP B ) and said attributive data (AS) related to the contour line from which the second cross point (CP B ) is obtained; (A10) comparing respective main scanning coordinate values of said first cross points (CP A ) to serially extract a first object point from said first cross points (CP A ), the order of the cross points being from said upstream side to said downstream side; (A11) comparing respective main scanning coordinate values of said second cross points (CP B ) to serially extract a second object point from said second cross points (CP B ) along said order; (A12) comparing respective main scanning coordinate values of said first and second object points to specify a cross point (CP) which is located at a position nearer to said upstream side within said first and second object points; (A13) selectively conducting the following steps (A13a) and A13b); (A13a) when the specified cross point (CP) which is specified in the step (A12) is said first object point, storing said attributive data (AS) of said first object point in a first memory means; (A13b) when said specified cross point (CP) is said second object point, deleting attributive data (AS) which is identical to said attributive data of said second object point from said first memory means; (A14) detecting a change in the maximum priority grade (P MAX ) within attributive data (AS) which is currently stored in said first memory means, said change being caused by the step (A13); (A15) in response to said change of said maximum priority grade (P MAX ) recovering the attributive data (AS) in said first memory means to whcih a changed maximum priority grade (P MAX ) corresponds; (A16) generating a component of said raster data on the basis of said imaging condition (CD) corresponding to said attributive data (AS) which is recovered in the step (A15) and said main scanning coordinate value of said specified cross point (CP); (A17) repeating the steps (A11) through (A16) until all of said first and second cross points are extracted in the step (A11) to generate components of said raster data for said scanning line (1), and (A18) repeating the steps (A6) through (A17) for each scanning line (1) in a subscanning direction to generate said raster data. A method according to Claim 1, wherein a combination of the steps (A6) and (A7) is conducted in parallel with a combination of the steps (A8) and (A9). A method according to Claim 1 or Claim 2, wherein the step (A10) further comprises the steps of: (A101) sorting respective first cross point data (D CA ) for said first cross points (C PA ) according to respective main scanning coordinate values of said first cross point data (D CA ) to store the sorted first cross point data (D CA ) in a second memory means, and (A102) serially reading out said sorted first cross point data (D CA ) from said second memory means in order along said scanning line to serially provide said first object point, and the step (A11) further comprises the steps of: (A111) sorting respective second cross point data (D CB ) for said second cross points (CP B ) according to respective main scanning coordinate values in said second cross point data (D CB ) to store the sorted second cross point data (D CB ) in a third memory means, and (A112) serially reading out said sorted second cross point data (D CB ) from said third memory means in said order along said scanning line to serially provide said seocnd object point. A method according to any one of Claims 1 to 3, further comprising the steps of: (A19) comparing a first main scanning coordinate value of said specified cross point (CP) with a second main scanning coordinate value of the most recently calculated component of said raster data; (A20) in the case where said first and second scanning coordinate values are different, comparing a first imaging condition (CD) for said specified cross point (CP) with a second imaging condition (CD) included in said most recently calculated component, and (A21) in the case where said first and second imaging conditions are identical, deleting said most recently calculated component from said first memory means. A method according to any one of the preceding claims, wherein the priority grade (P k ) is commonly assigned to two or more grade figures. A method according to Claim 5, wherein said priority grade (P k ) is selected from first through M-th priority grades where M is an integer larger than one, and the total number of said graphic figures (LP) is larger than the integer M. A method according to any one of Claims 4 to 6, further comprising the step of: (A22) in the case where said specified cross point (CP) is said first object point, and said maximum priority grade (P k ) is unchanged by the step (A13a), comparing a third imaging condition of said specified cross point (CP) with a fourth imaging condition included in the most recently calculated component of said raster data to generate a new component of said raster data on the basis of said main scanning coordinate value of said specified cross point (CP) and said third imaging condition only when said third imaging condition is at a higher priority (P) than said fourth imaging condition according to a predetermined priority rule of imaging conditions. A method according to Claim 7, further comprising the step of: (A23) in the case where said specified point (CP) is said second object point, and said maximum priority grade (P k ) is unchanged by the step (A13b), comparing said third imaging condition with a fifth imaging condition included in said attributive data which remains in said first memory means and has said maximum priority grade after the step (A13b) is completed, to generate a new component of said raster data on the basis of said main scanning coordinate value of said specified cross point (CP) and said fifth imaging condition only when said third imaging condition is at a higher priority (P) than said fifth imaging condition according to said priority rule. A method according to Claim 8, wherein said method further comprises the step of: (A24) preparing first through N-th counter means which are assigned to said first through N-th priority grades (P k ), respectively, the step (A13a) includes the step of; incrementing one of said first through N-th counter means corresponding to a priority grade (P k ) of said specified cross point (CP) when said specified cross point (CP) is said first object point, the step (A13b) includes the step of; decrementing one of said first through N-th counter means corresponding to said priority grade (P k ) of said specified cross point (CP) when said specified cross point (CP) is said second object point, and the step (A14) includes the step of; referring to said first through N-th counter means to find said change of said maximum priority grade (P k ). A method according to Claim 9, wherein said contour lines are contour vectors whose directionality are so determined that an internal region of a graphic figure (LP) exists on one side of each contour vector, and the step (A5) includes the steps of: detecting respective directions of said contour vectors classifying said contour vectors into said first and second groups according to said directions. A method according to Claim 10, wherein each of said contour vectors is expressed by vector data (DV) having respective coordinate values of terminal points of the contour vector the step (A4) includes the step of adding said attributive data (AS) to the corresponding vector data (DV), and said contour lines which are classified in the step (A5) are expressed by said vector data (Dv) and said attributive data (AS). A method according to Claim 11, wherein a plurality of contour vectors which belong to the same group as said first and second groups and are connected in series on a contour of a graphic figure (LP) are combined with each other in said vector data (Dv). A method according to Claim 12, wherein said priority grade (Pk) is assigned to each graphic figure regardless of respective imaging conditions (CD) of said graphic figures (LP).

Inventors: HIKITA AKIRA - TENJINKITAMACHI, HIRAWA TAKAHIDE - TENJINKITAMA, KAGO YOSHIKAZU - TENJINKITIMAC, MATSUDA HITOSHI - TENJINKITAMA, HIKITA, AKIRA 1-1, TENJINKITAMACHI, HIRAWA, TAKAHIDE 1-1, TENJINKITAMACHI, KAGO, YOSHIKAZU1-1, TENJINKITIMACHI, MATSUDA, HITOSHI 1-1, TENJINKITAMACHI
Applicants: DAINIPPON SCREEN MFG, DAINIPPON SCREEN MFG. CO., LTD.
Application year: 1989
Main classification: G06F15
IPC codes: G06T1, H04N1, G06K15, G06T11