Image matching system

Abstract: A figure location detecting system is designed to detect a location of a first figure (e.g., search fingerprint) within a second figure (e.g., file fingerprint). Particularly, the system is designed to correctly match characteristic points of the first figure with characteristic points of the second figure even if the first figure contains a plenty of similar characteristic points whose characteristics are similar with each other and/or even if the first figure is (partially) distorted. Herein, the system creates matching characteristic point pair candidates each corresponding to a pair of a first characteristic point, corresponding to one of the characteristic points of the first figure, and a second characteristic point corresponding to one of the characteristic points of the second figure. The matching characteristic point pair candidates are created on the basis of relative characteristics which are calculated for proximity characteristic points which exist in proximity to the first and second characteristic points respectively. Then, the system narrows down the matching characteristic point pair candidates to matching characteristic point pairs by removing wrong matching characteristic point pair candidates, each of which is detected as a wrong match in consideration of a matching situation of the proximity characteristic points. Coordinate matching parameters are produced with respect to each of the matching characteristic point pairs. Thus, the system outputs most concentrated coordinate matching parameters which values of the coordinate matching parameters sequentially produced concentrate in most frequently (Fig. 1).

Description: This invention relates to image matching systems which detect positional relationships between figures to be matched with each other. Conventionally, there is provided technology to detect a positional relationship between figures, in other words, technology to perform detection as to which location (or part) of a second figure a first figure matches with. This technology is used for the figure matching devices which perform the matching process with respect to fingerprints and aerial photographs. For example, the paper of JP 5181949 A (denoted by "paper 1") discloses an image positioning device corresponding to one example of the above technology conventionally known. According to this, an airplane equipped with a photographing machine flies over some terrestrial areas to take geomorphologic pictures, from which a matched picture being subjected to the matching process with another picture is obtained. Then, the device detects a positional correspondence between positional coordinates of the matched picture and the map coordinates which are determined in advance. In the conventional system, characteristic points are extracted from the matched picture and are subjected to affine transformation using an affine coefficient which is set in advance. Thus, the matched picture is transformed to conform with the map coordinate system. The point pattern matching is performed between "matching" characteristic points, which are used as reference for the matching process (or pattern matching), and matched characteristic points which are obtained by the affine transformation of the characteristic points to conform with the map coordinate system. Thus, it is possible to provide matching characteristic point pair candidates through the point pattern matching. Thereafter, the system performs processes similar to the aforementioned processes with respect to each of the matching cases while changing the affine coefficient by a prescribed interval of value. Those processes are repeated until the affine coefficient, which is changed every time the processes are performed with respect to each of the matching cases, leaves a prescribed range. When execution of the processes is ended because the affine coefficient leaves the prescribed range, the conventional system selects a matching case in which the number of the matching characteristic point pair candidates is the largest from among the aforementioned matching cases. Coordinate values of the matching characteristic point pair candidates in the selected matching case are placed into a transformation equation representing a coordinate relationship between two figures. Thus, the system produces a coefficient of the above transformation equation. According to the conventional technology described above, the matched picture corresponds to an aerial photograph taken by the photographing machine whose dip and photographing direction are roughly determined in advance. In other words, the conventional technology is not designed in consideration of the situation where the direction of the matched picture is uncertain. So, the conventional technology is inapplicable to the situation where the direction of the matched picture is uncertain. In addition, the conventional technology handles the whole area of the matched picture by using single affine transformation. So, the conventional technology is inapplicable to the situation where the matched picture is partially distorted. Further, the conventional technology is designed such that the coordinate values of the matching characteristic point pair candidates are placed into the transformation equation to produce the coefficient of the transformation equation. So, if an error is included in the matching characteristic point pair candidates which are used to produce the coefficient of the transformation equation, there is a high risk that the produced coefficient of the transformation equation becomes incorrect. Meanwhile, the fingerprint matching technology introduces a concept in definition of the center of the fingerprint pattern. The conventional technology uses such a concept to match characteristic points of a search fingerprint with characteristic points of a file fingerprint with respect to the coordinate system. One example of this technology is disclosed by the paper (denoted by "paper 2") of the monographic journal of the Institute of Electronics, Information and Communication Engineers of Japan, Volume J72-DII, No. 5, pp.733-740 issued on May of 1989, for example. However, this technology is inapplicable to the picture, such as the palm print, which does not contain a pattern which can be defined as the center. The paper of Japanese Patent Publication No. JP 59 000 793 (denoted by "paper 3") discloses another example of the above technology. According to the above, the system finds out the characteristic point of the search fingerprint and the characteristic point of the file fingerprint, which are similar each other with respect to an amount of local characteristics. Those characteristic points are connected with each other as a matching characteristic point pair candidate. Then, the system calculates a similarity score for the above matching characteristic point pair candidate. Incidentally, an amount of local characteristics is defined by the kind(s) of the characteristic points or a number of characteristic points which exist within a certain radius range of the figure. Suppose a local coordinate system in which characteristic point is used as an origin of the coordinates while the direction of the characteristic point is represented by a Y axis. Herein, an amount of local characteristics is defined by a number of other characteristic points which are distributed in each of the quadrants of the local coordinate system or a number of ridge lines which intervene between the characteristic point in each quadrant of the local coordinate system and its closest characteristic point. Thereafter, the system rotates the search fingerprint by a certain angle of rotation. Then, the following processes are performed with respect to each characteristic point of the rotated search fingerprint, as follows: The system selects one of the characteristic points of the rotated search fingerprint. The file fingerprint has characteristic points, one of which is connected with the above characteristic point selected by the system. So, the system calculates differences between X, Y coordinate values of the selected characteristic point and X, Y coordinate values of the connected characteristic point of the file fingerprint. Being connected with the differences, the system records a similarity score calculated for a pair of the above characteristic points on a recording media. Thereafter, the system selects another characteristic point from among the characteristic points of the search fingerprint which are not selected. So, the system performs processes similar to the foregoing processes on the newly selected characteristic point. In this case, the system calculates differences with regard to the newly selected characteristic point. If the differences newly calculated exist in the pre-calculated differences which have been already calculated, a similarity score calculated for a pair of characteristic points is accumulated with the similarity score which has been already recorded with being connected with the pre-calculated differences. The above processes are repeatedly performed with respect to all of the characteristic points of the search fingerprint. Thereafter, the system selects a highest similarity score (i.e., maximum weighting factor) from among the similarity scores which are recorded. In addition, the system calculates differences which are connected to the highest similarity scores. So, the system records the maximum weighting factor and differences on a recording media. Next, the system rotates the search fingerprint again. So, the system performs processes similar to the foregoing processes with respect to the rotated search fingerprint. Thus, the system calculates a maximum weighting factor as well as differences which are connected to the maximum weighting factor with respect to the rotated search fingerprint. Then, the system compares the "present" maximum weighting factor which is presently calculated with the "previous" maximum weighting factor which has been previously calculated but which remains now. Only when the present maximum weighting factor is greater than the previous maximum weighting factor, the system renews recorded values with values corresponding to the differences and maximum weighting factor which are presently calculated. By repeating the foregoing processes, it is possible to obtain a rotation angle of the search fingerprint which makes the maximum weighting factor to be really maximal as well as differences regarding X, Y coordinates values. The above rotation angle is used as a best rotation angle that establishes a best matching state between the characteristic points of the search fingerprint and the characteristic points of the file fingerprint. In addition, the differences which are calculated with respect to the above rotation angle are used as an amount of parallel displacement (or parallel translation). In short, the conventional technology described above performs calculations and matching processes while rotating the search fingerprint, which is a searched picture subjected to search, by a certain angle, so it produces differences regarding X, Y coordinate values with respect to a certain rotation angle of the search fingerprint that makes the maximum weighting factor to be really maximal. The above rotation angle and differences are used as the best rotation angle and parallel displacement respectively, which establish a best matching state between the characteristic points of the search fingerprint and the characteristic points of the file fingerprint. Thus, this technology is applicable to the picture whose direction is uncertain and the picture which does not have a pattern defining the center. In addition, this technology is applicable to the situation where a wrong matching characteristic point pair candidate is included in the matching characteristic point pair candidates. The aforementioned paper 3 does not at all provide a concrete description as to the method (or technique) how to obtain the matching characteristic point pair candidates between the characteristic points of the searched picture and the characteristic points of the file picture. According to the technology described in the paper 3, even if the system selects wrong matching characteristic point pair candidates which are wrongly proposed to some extent, the system is capable of producing "correct" coordinate matching parameters (i.e., rotation angle and parallel displacement). However, if the system selects a number of wrong matching characteristic point pair candidates, there is a high risk that the system produces "incorrect" coordinate matching parameters. In general, when there exist a plenty of characteristic points whose characteristics are similar each other within the searched picture, a risk that the system selects a plenty of wrong matching characteristic point pair candidates becomes higher. So, the foregoing conventional technology must suffer from an increased risk that incorrect coordinate matching parameters are produced when a plenty of characteristic points whose characteristics are similar each other exist within the searched picture. In addition, the above technology is not designed in consideration of the situation where the searched picture contains distortion. So, when using the distorted picture (or partially distorted picture) as the searched picture, the conventional technology suffers from a problem that incorrect coordinate matching parameters are produced. In US-A-4 135 147, a system is disclosed which comprises first means responsive to minutiae of first and second fingerprints for selectively generating a plurality of neighborhood comparison signals indicative of a closeness of match and coordinate displacements between minutiae neighborhoods of the first and second fingerprints, and second means responsive to the neighborhood comparison signals for developing an output signal indicative of the relative closeness of match of the first and second fingerprints. EP-A-0 300 167 describes an apparatus and method for matching images in which characteristic points of an image to be tested for a match, such as a fingerprint, are compared with characteristic points of a master image by attempting to match the distances between pairs of master characteristic points with distances between pairs of live characteristic points. It is an object of the invention to provide a figure location detecting system which detects a positional relationship between figures so as to correctly produce coordinate matching parameters, representing the matching between coordinates of figures, even if a searched figure is partially distorted or even if a searched figure contains a plenty of similar characteristic points whose characteristics are similar each other. This object is achieved with the features of the claims. An image matching system of this invention is designed to detect a location of a first figure (i.e. configuration, e.g., search fingerprint) within a second figure (e.g., file fingerprint). Particularly, this invention is designed to correctly match characteristic points of the first figure with characteristic points of the second figure even if the first figure contains a plenty of similar characteristic points whose characteristics are similar with each other and/or even if the first figure is (partially) distorted. At first, the image matching system creates matching characteristic point pair candidates each corresponding to a pair of a first characteristic point, corresponding to one of the characteristic points of the first figure, and a second characteristic point corresponding to one of the characteristic points of the second figure. The matching characteristic point pair candidates are created on the basis of relative characteristics which are calculated for proximity characteristic points which exist in proximity to the first and second characteristic points respectively. Then, the system narrows down the matching characteristic point pair candidates to matching characteristic point pairs by removing wrong matching characteristic point pair candidates, each of which is detected as a wrong match in consideration of a matching situation of the proximity characteristic points. Coordinate matching parameters are produced with respect to each of the narrowed matching characteristic point pairs. The coordinate matching parameters contain coordinate values and a direction of the characteristic point on a coordinate system, the origin of which is determined based on coordinate values of the characteristic point and an axis of which is determined based on an amount of characteristics of the characteristic point. Thus, the system outputs the coordinate matching parameters which occur most frequently. These and other objects of the subject invention will become more fully apparent as the following description is read in light of the attached drawings wherein: FIG. 1 is a block diagram showing an example of a configuration of an image matching system in accordance with the embodiment of the invention; FIG. 2 is a flowchart showing processes of the image matching system of FIG. 1; FIG. 3 is a flowchart showing processes for creation of matching characteristic point pair candidates; FIG. 4 shows an example of arrangement of proximity characteristic points which exist in proximity to a characteristic point of a search fingerprint; FIG. 5 shows an example of arrangement of proximity characteristic points which exist in proximity to a characteristic point of a file fingerprint; FIG. 6 shows relationships between amounts of relative characteristics of the proximity characteristic points shown in FIG. 4 and amounts of relative characteristics of the proximity characteristic points shown in FIG. 5; FIG. 7 shows another example of arrangement of proximity characteristic points which exist in proximity to a characteristic point of a file fingerprint; and FIG. 8 shows relationship between amounts of relative characteristics of the proximity characteristic points shown in FIG. 4 and amounts of relative characteristics of the proximity characteristic points shown in FIG. 7. Now, a description will be given with respect to the preferred embodiment of the invention in conjunction with drawings. FIG. 1 shows a configuration of an image matching system in accordance with the preferred embodiment of the invention. This system is configured mainly by an input device 1, a data processing device 2, an output device 3 and a recording media 4. Herein, the input device 1 is configured using a keyboard and a storage unit such as a hard-disk unit, a floppy-disk unit and a compact disc unit; the data processing device 2 is configured by a computer which operates under the control of programs; and the output device 3 is configured using a display unit and a printer as well as a storage unit such as a hard-disk unit and a floppy-disk unit. The input device 1 has functions which are represented by two blocks, i.e., a first figure characteristic point input block 11 and a second figure characteristic point input block 12. The first figure characteristic point input block 11 produces an amount of characteristics with respect to each of characteristic points which exist in a first figure corresponding to a searched figure to be subjected to search, so the amount of characteristics is input to the data processing device 2. The second figure characteristic point input block 12 produces an amount of characteristics with respect to each of characteristic points which exist in a second figure, so the amount of characteristics is input to the data processing device 2. The data processing device 2 contains a matching characteristic point pair candidate creation block 21, a matching characteristic point pair candidate narrowing block 22 and a figure location determination block 23. The matching characteristic point pair candidate creation block 21 refers to characteristic points of the second figure so as to extract a characteristic point, which has a possibility of being assumed as equivalence of a characteristic point of the first figure and which is connected with a characteristic point of the first figure. Thus, the block 21 provides a pair of the characteristic points connected with each other as a matching characteristic point pair candidate. Herein, a decision as to whether the characteristic points can be connected with each other is made based on amounts of relative characteristics each calculated for each of proximity characteristic points which exist in proximity to the characteristic point within a prescribed range of distance. Incidentally, the amount of relative characteristics depends on a relationship between the characteristic point and its proximity characteristic point. The matching characteristic point pair candidate narrowing block 22 removes a wrong matching characteristic point pair candidate, which is considered to be wrongly matched with the characteristic point. A decision to choose the wrong matching characteristic point pair candidates is made based on the matching situation with respect to the proximity characteristic points. Thus, the block 22 removes characteristic points, each of which is considered as a wrong match on the basis of the matching situation of the proximity characteristic points, from pairs of characteristic points which are proposed as the matching characteristic point pair candidates by the matching characteristic point pair candidate creation block 21. Thus, the block 22 outputs remaining pairs of characteristic points as matching characteristic point pairs. Using the matching characteristic point pairs which are narrowed down by the matching characteristic point pair candidate narrowing block 22, the figure location determination block 23 produces coordinate matching parameters to match the first figure with the second figure. The data processing device 2 is equipped with the recording media 4 which records an image matching program. As the recording media 4, it is possible to employ a magnetic disk, semiconductor memory and other recording media. The data processing device 2 loads the image matching program recorded on the recording media 4. By controlling the operation of the data processing device 2 based on the image matching program, it is possible to realize functions of the matching characteristic point pair candidate creation block 21, the matching characteristic point pair candidate narrowing block 22 and the figure location determination block 23 on the processing of the data processing device 2. Next, a description will be given with respect to operations of the data processing device 2 in conjunction with FIG. 2 and FIG. 3. Herein, FIG. 2 shows a flow of steps with respect to an example of overall processing of the data processing device 2, while FIG. 3 shows a flow of steps with respect to an example of processing regarding creation of matching characteristic point pair candidates by the matching characteristic point pair candidate creation block 21. In step A1 shown in FIG. 2, the first figure characteristic point input block 11 inputs amounts of characteristics of characteristic points of the first figure into the data processing device 2. In step A2, the second figure characteristic point input block 12 inputs amounts of characteristics of characteristic points of the second figure into the data processing device 2. Then, the matching characteristic point pair candidate creation block 21 of the data processing device 2 makes a decision as to which of the characteristic points of the second figure each of the characteristic points of the first figure matches with. Using results of the decision, the block 21 creates a matching characteristic point pair candidate list P in step A3. Details of the step A3 are shown in FIG. 3. In step A11, the block 21 designates a single characteristic point from a set R of the characteristic points of the first figure, so the designated characteristic point is denoted by a symbol "a". In step A12, the block 21 designates a single characteristic point from a set S of the characteristic points of the second figure, so the designated characteristic point is denoted by a symbol "b". In step A13, an examination is performed as to a possibility that the characteristic point "a" corresponds to the characteristic point "b" or a possibility that the characteristic point "a" is connected with the characteristic point "b". A decision as to whether the possibility that the characteristic point "a" corresponds to the characteristic point "b" is made based on amounts of relatively characteristics calculated for proximity characteristic points, which exist in proximity to the characteristic point "a", and amounts of relative characteristics of proximity characteristic points which exist in proximity to the characteristic point "b". Herein, an amount of relatively characteristics depends on a relationship between the characteristic point and its proximity characteristic point. That is, an amount of relative characteristics which is calculated with respect to each of proximity characteristic points which exist in proximity to the characteristic point "a" is compared with an amount of relative characteristics which is calculated with respect to each of proximity characteristic points which exist in proximity to the characteristic point "b". Herein, a decision is made as to whether a difference between the amounts of the relative characteristics meets a prescribed allowable error range or not. Then, the block 21 detects pairs of proximity characteristic points which meet the prescribed error range. If a number of the pairs of the proximity characteristic points which meet the prescribed allowable error range is greater than a threshold number which is determined by a total number of the proximity characteristic points, the block 21 detects a possibility that the characteristic point "a" corresponds to the characteristic point "b". As the above threshold number, it is possible to use a number which is produced by multiplying a total number of proximity characteristic points of the characteristic point "a" by a prescribed value α (where 0<α<1). Further, it is possible to use a number which is produced by multiplying a total number of proximity characteristic points of the characteristic points "a" and "b" by a prescribed value α. If the block 21 makes a decision in steps A13 and A14 that there is a possibility that the characteristic point "a" corresponds to the characteristic point "b", the block 21 proceeds to step A15 via step A14, wherein a pair of the characteristic points "a" and "b" are added to the matching characteristic point pair candidate list P. Thereafter, the block 21 repeats the step A12. If the block makes a decision that there is no possibility that the characteristic points are considered to be identical to each other, in other words, if a result of the decision of the step A14 is "NO", the block 21 repeats the step A12. The aforementioned steps are repeated until both of decision results of steps A16 and A17 turn to "YES". Namely, the aforementioned steps are repeated with respect to all of combinations of the characteristic points of the first and second figures. When the matching characteristic point pair candidate creation block 21 creates the matching characteristic point pair candidate list P containing the matching characteristic point pair candidates, a decision result of the step A4 of the data processing device 2 turns to "YES". So, the matching characteristic point pair candidate list P is passed to the matching characteristic point pair candidate narrowing block 22. On the other hand, if the list P is not created, in other words, if the decision result of the step A4 is "NO", the data processing device outputs a message representing incapability of detection of figure location in step A5. This message is output to the output device 3. The matching characteristic point pair candidate narrowing block 22 refers to the matching situation of the proximity characteristic points so as to detect a wrong matching characteristic point pair candidate which is considered as a wrong match. So, the block 22 removes the wrong matching characteristic point pair candidate from the matching characteristic point pair candidates listed in the matching characteristic point pair candidate list P, thus providing remained matching characteristic point pair candidates, which are registered in a matching characteristic point pair list Q as matching characteristic point pairs in step A6. The detailed explanation of the step A6 is as follows: At first, the device designates a matching characteristic point pair candidate which is registered in the matching characteristic point pair candidate list P. With regard to the designated matching characteristic point pair candidate, the device searches all of proximity characteristic points which exist in proximity to characteristic points of the first and second figures. Then, an amount of relative characteristics of the proximity characteristic point of the first figure is compared with an amount of relatively characteristics of the proximity characteristic point of the second figure. So, the device produces all of pairs of proximity characteristic points whose differences in amounts of relative characteristics meet a prescribed allowable error range. Incidentally, this prescribed allowable error range is identical to the allowable error range which is used by the mathing characteristic point pair candidate creation block 21. Thereafter, searching is performed on the matching characteristic point pair candidate list P, so an examination is performed as to whether the produced pairs of proximity characteristic points are registered in the matching characteristic point pair candidate list P. If a number of the pairs of the proximity characteristic points registered in the matching characteristic point pair candidate list P is greater than a prescribed rate of a total number of the produced pairs of the proximity characteristic points, the designated matching characteristic point pair candidate which the device designates is registered in the matching characteristic point pair list Q as a matching characteristic point pair. In short, if pairs of proximity characteristic points, differences of relative characteristics of which meet the allowable error range and which are used for making a decision as to whether a pair of characteristic points corresponding to the presently designated matching characteristic point pair candidate should be registered in the matching characteristic point pair candidate list P or not, are registered in the list P by more than a prescribed rate, the matching characteristic point pair candidate creation block 21 registers the presently designated matching characteristic point pair candidate in the matching characteristic point pair list Q as the matching characteristic point pair. The aforementioned processes are repeatedly performed with respect to all of matching characteristic point pair candidates which are registered in the matching characteristic point pair candidate list P. In the flowchart of FIG. 2, the step A6 is executed only one time. However, if it is demanded to further narrow down the matching characteristic point pairs to correct ones, the matching characteristic point pair list Q is used as the matching characteristic point pair candidate list P so that the aforementioned processes are performed again by one or more times. Herein, the device detects proximity characteristic point pairs, whose differences in amounts of relatively characteristics meet the allowable error range, with respect to each of the matching characteristic point pairs registered in the matching characteristic point pair list Q. So, an examination is made as to whether a number of the above proximity characteristic point pairs occupy a prescribed rate or more of a total number of the pairs registered in the matching characteristic point pair list Q or not. Thus, the device lists matching characteristic point pairs each related to proximity characteristic point pairs, a number of which is greater than the prescribed rate of the total number of pairs registered in the list Q, so as to register them in another matching characteristic point pair list, which is denoted by Q1, for example. In the data processing device 2, if the matching characteristic point pair candidate narrowing block 22 creates the matching characteristic point pair list Q containing the matching characteristic point pairs, in other words, if a decision result of the step A7 is "YES", the matching characteristic point pair list Q is passed to the figure position determination block 23. If the list Q is not created, in other words, if the decision result of the step A7 is "NO", the data processing device 2 outputs a message declaring the incapability of detection of image matching. The message is output to the output device 3 in step A5. When receiving the matching characteristic point pair list Q, the figure location determination block 23 produces coordinate matching parameters to overlap the matching characteristic point pairs registered in the list Q in step A8. Then, the coordinate matching parameters are output to the output device 3 in step A9. Detailed explanation of the step A8 is as follows: At first, the device designates a matching characteristic point pair registered in the matching characteristic point pair list Q. Then, the device calculates an angle difference between two characteristic points included in the designated matching characteristic point pair as well as coordinate differences of X, Y coordinate values between the two characteristic points. The calculated differences are paired each other and recorded on a recording media. The above processes are repeatedly performed with respect to all of the matching characteristic point pairs registered in the matching characteristic point pair list Q. Among the recorded pairs of the differences, the device selects a pair of differences which calculation results concentrate in most frequently. So, the angle difference and coordinate differences of X, Y coordinate values of the most concentrated pair are used to form coordinate matching parameters. Incidentally, it is not necessary to use the most concentrated pair only for formation of the coordinate matching parameters. For example, a prescribed number of pairs, which count from the most concentrated pair, are selected, so that the angle differences and coordinate differences thereof are used for formation of coordinate matching parameters. Next, the operation of the image matching system of FIG. 1 will be explained more precisely in conjunction with an example where a search fingerprint is used for the first figure while a file fingerprint is used for the second figure. In ridge line figures such as the fingerprints and palm prints, it is possible to use end points, at which ridge lines break off, and branch points, at which ridge lines branch off, as characteristic points. So, positions of the characteristic points as well as contact directions of the characteristic points which are placed in contact with the ridge lines can be used as amounts of characteristics. In addition, curvature as well as a number of ridge lines between characteristic points can be added to the amounts of characteristics. In the case where the search fingerprint is used for the first figure while the file fingerprint is used for the second figure, the first figure characteristic point input block 11 inputs an amount of characteristics, which is produced with respect to each of characteristic points of the search fingerprint, to the data processing device 2 in step A1 of FIG. 2. In addition, the second figure characteristic point input block 12 inputs an amount of characteristics, which is produced with respect to each of characteristic points of the file fingerprint, to the data processing device 2 in step A2. Thus, the matching characteristic point pair candidate creation block 21 operates in accordance with processes of the aforementioned flowchart of FIG. 3. That is, the block 21 designates a characteristic point from among the set R of the characteristic points of the search fingerprint, so that the designated characteristic point is denoted by the symbol "a" in step A11. In addition, the block 21 designates a characteristic point from among the set S of the characteristic points of the file fingerprint, so that the designated characteristic point is denoted by the symbol "b" in step A12. Then, the matching characteristic point pair candidate creation block 21 performs an examination as to a possibility that the characteristic points "a" and "b" correspond to each other in step A13. Herein, the examination is performed using amounts of relative characteristics which are produced with respect to proximity characteristic points of the characteristic points "a" and "b". Next, the process of the step A13 will be explained in detail. FIG. 4 shows an example where proximity characteristic points a1, a2, a3 exist in proximity to the characteristic point a. FIG. 5 shows an example where proximity characteristic points b1, b2, b3 exist in proximity to the characteristic point b. As shown in FIG. 4 and FIG.5, proximity characteristic points are defined as characteristic points which exist in a circle of a radius r formed about the subject characteristic point. In step A13, the matching characteristic point pair candidate creation block 21 firstly calculates an amount of relative characteristics with respect to each of the proximity characteristic points a1, a2, a3 which exist in proximity to the characteristic point a. Herein, an X-Y coordinate system is established such that the characteristic point a is used as an origin while a contact direction of the characteristic point a which is placed in contact with the ridge line is used as a Y axis. So, an amount of relative characteristics is produced using the coordinate values and contact direction with respect to each of the proximity characteristic points a1, a2, a3. Incidentally, it is possible to establish another X-Y coordinate system in which a point having a prescribed relationship with the characteristic point a is used as an origin while a direction having a prescribed relationship with the contact direction of the characteristic point a placed in contact with the ridge line is used as an X axis or a Y axis. Using such an X-Y coordinate system, it is possible to produce an amount of relative characteristics using the coordinate values and contact direction with respect to each of the proximity characteristic points a1, a2, a3. In addition, a number of ridge lines, which exist between the characteristic point a and each of the proximity characteristic point a1, a2, a3, can be added to the amount of relative characteristics. Further, curvature of the ridge line measured at a position of the proximity characteristic point can be added to the amount of relative characteristics. Next, the matching characteristic point pair candidate creation block 21 produces an amount of relative characteristics with respect to each of the proximity characteristic points b1, b2, b3 which exist in proximity to the characteristic point b. Thereafter, the matching characteristic point pair candidate creation block 21 compares an amount of relative characteristics, produced for each of the proximity characteristic points a1, a2, a3, with an amount of relative characteristics produced for each of the proximity characteristic points b1, b2, b3. So, the block 21 searches a pair of the proximity characteristic points whose difference in the amount of relative characteristics meets a prescribed allowable error range. As a result, the block 21 sequentially finds out multiple pairs which meet the above. If a number of the pairs found out is greater than a threshold number which is determined based on a total number of the proximity characteristic points a1, a2, a3 which exist in proximity to the characteristic point a, the block determines that there is a possibility that the characteristic point a corresponds to the characteristic point b. If not, the block determines that there is no possibility. Suppose the example of FIG. 4 that the proximity characteristic points a1, a2, a3 are arranged in proximity to the characteristic point a as well as the example of FIG. 5 that the proximity characteristic points b1, b2, b3 are arranged in proximity to the characteristic point b. FIG. 6 shows relationships between the amounts of relative characteristics of the proximity characteristic points a1, a2, a3 and the amounts of relative characteristics of the proximity characteristic points b1, b2, b3. In that case, all of differences between the amounts of relative characteristics of the proximity characteristic points a1, a2, a3 and the amounts of relative characteristics of the proximity characteristic points b1, b2, b3 meet the allowable error range which is prescribed in advance. So, the device makes a decision that there is a possibility that the characteristic point a matches with the characteristic point b. Suppose another example of FIG. 7 that proximity characteristic points b1, b2, b3, b4 are arranged in proximity to the characteristic point b. Using FIG. 4 and FIG. 7, FIG. 8 shows relationships between the amounts of relative characteristics of the proximity characteristic points a1, a2, a3 and amounts of relative characteristics of the proximity characteristic points b1, b2, b3, b4. In the case of FIG. 8, there exists no pair of the proximity characteristic points whose difference in amount of relative characteristics meets the allowable error range. So, the device makes a decision that there is no possibility that the characteristic point a matches with the characteristic point b. If the device makes a decision that there is a possibility that the characteristic point a corresponds to the characteristic point b, in other words, if a decision result of step A14 is "YES", a pair of the characteristic points a, b are registered in the matching characteristic point pair candidate list P in step A15. Thereafter, the step A12 is performed again. If the device makes a decision that there is no possibility that the characteristic points correspond to each other, in other words, if the decision result of step A14 is "NO", the device repeats the step A12 immediately. The matching characteristic point pair candidate creation block 21 repeats the aforementioned processes until both of decision results of steps A16, A17 turn to "YES". If the matching characteristic point pair candidate creation block 21 creates the matching characteristic point pair candidate list P including the matching characteristic point pair candidates, in other words, if a decision result of step A4 is "YES", the data processing device 2 passes the list P to the matching characteristic point pair candidate narrowing block 22. If the block 21 does not create the list P, in other words, if the decision result of step A4 is "NO", the device 2 provides a message representing incapability of detection of image matching, which is output to the output device 3 in step A5. As described before, the matching characteristic point pair candidate narrowing block 22 detects the wrong matching characteristic point pair candidate based on the matching state of the proximity characteristic points, so the block 22 removes it from the matching characteristic point pair candidates of the matching characteristic point pair candidate list P. Then, the block 22 registers remaining pairs in the matching characteristic point pair list Q as matching characteristic point pairs in step A6. If the matching characteristic point pair candidate narrowing block 22 creates the matching characteristic point pair list Q containing the matching characteristic point pairs, in other words, if a decision result of step A7 is "YES", the data processing device 2 passes the list Q to the figure location determination block 23. If the block 22 does not create the list Q, in other words, if the decision result of step A7 is "NO", the device 2 provides a message of incapability of detection of image matching, which is output to the output device 3 in step A5. When receiving the matching characteristic point pair list Q, the figure location determination block 23 proceeds to step A8 to perform processes, as follows: At first, the figure location determination block 23 designates a matching characteristic point pair registered in the matching characteristic point pair list Q. Now suppose an example that the block 23 extracts (or designates) a matching characteristic point pair consisting of a characteristic point "g" of a search fingerprint and a characteristic point "h" of a file fingerprint. In this example, the figure location determination block 23 produces coordinate matching parameters representing an amount of rotation and an amount of parallel displacement by which the characteristic point g is subjected to rotation and parallel displacement so that the characteristic point g is moved to match with the characteristic point h with respect to coordinates. Thereafter, the figure location determination block 23 extracts another matching characteristic point pair registered in the matching characteristic point pair list Q, so it performs processes similar to the above ones with respect to the extracted pair. After completion of the above processes with respect to all of the matching characteristic point pairs registered in the matching characteristic point pair list Q, the figure location determination block 23 totals the coordinate matching parameters. Herein, the block 23 selects the coordinate matching parameters whose frequency in occurrence is the highest. So, the block 23 determines the selected coordinate matching parameters to be output. In step A9, the figure location determination block 23 outputs the coordinate matching parameters, which are determined by the step A8, to the output device 3. Lastly, the effects of the invention can be summarized as follows: Even if the first figure corresponding to the searched picture contain a plenty of similar characteristic points whose amounts of characteristics are similar to each other, or even if the first figure contain distortion, it is possible to produce "correct" coordinate matching parameters, because, this invention is designed to make a decision, based on amounts of relative characteristics of proximity characteristic points, as to whether the characteristic points are chosen as the matching characteristic point pair candidates. In addition, this invention is designed to narrow down the matching characteristic point pairs on the basis of a result of a decision as to whether proximity characteristic point pairs, which are used for the decision whether to choose the characteristic points as the matching characteristic point pair candidates, are contained in the matching characteristic point pair candidates by more than a prescribed rate or not. That is, even if the first figure is distorted, this invention sets a narrow range corresponding to the proximity characteristic points so that the distortion can be neglected. Further, even if an amount of information regarding amounts of characteristics is small because of the setting of the narrow range of the proximity characteristic points, it is possible to narrow down the matching characteristic point pairs under a state of an increased amount of information because this invention is designed to narrow down the matching characteristic point pairs on the basis of a result of a decision as to whether the matching characteristic point pair candidates contain the proximity characteristic point pairs, used for the decision whether to choose the characteristic points as the matching characteristic point pair candidates, by more than a prescribed rate or not. So, even if the first figure contains a plenty of similar characteristic points, it is possible to reduce a risk that the narrowed matching characteristic point pairs, which are narrowed down, contain a wrong matching characteristic point pair which is considered as a wrong match. In addition, it is possible to further reduce a risk that the "final" matching characteristic point pair candidates, which are finally obtained, contain a wrong matching characteristic point pair candidate which is considered as a wrong match because this invention is designed to narrow down the matching characteristic point pair candidates multiple times. Further, even if the narrowed matching characteristic point pairs contain error, it is possible to produce "correct" coordinate matching parameters, because this invention is designed to output the most concentrated parameters within the coordinate matching parameters which are produced with respect to each of the matching characteristic point pairs. In other words, even if the narrowed matching characteristic point pairs contain a wrong matching characteristic point pair, the coordinate matching parameters calculated based on the wrong matching characteristic point pair must disperse in a variety of values while the coordinate matching parameters calculated based on the correct matching characteristic point pair converge on or around correct values. So, even if the matching characteristic point pairs contain error, it is possible to produce the correct coordinate matching parameters. As this invention may be embodied in several forms, the present embodiment is therefore illustrative and not restrictive, since the scope of the invention is defined by the appended claims rather than by the description preceding them.

Claims: An image matching method for locating a first figure, i.e. configuration, within a second figure by comparing characteristic points of the first figure with characteristic points of the second figure, said image matching method comprising the steps of: designating one of the characteristic points of the first figure as a first characteristic point (A1); designating one of the characteristic points of the second figure as a second characteristic point (A2) relative to the first characteristic point; calculating a first amount of relative characteristics for each of proximity characteristic point, which exist in proximity to the first characteristic point, on the basis of a relationship between the first characteristic point and each of the proximity characteristic points; calculating a second amount of relative characteristics for each of proximity characteristic points, which exist in proximity to the second characteristic point, on the basis of a relationship between the second characteristic point and each of the proximity characteristic points; determining whether or not the first amount of relative characteristics matches the second amount of relative characteristics within a prescribed allowable range of error; sequentially detecting pairs of the first and second characteristic points, the amounts of relative characteristics of which do not exceed the allowable range of error and the number of which is greater than a predetermined number, so that the detected pairs of the first and second characteristic points are used as matching characteristic point pairs candidates (A3); narrowing down (A6) the matching characteristic point pair candidates to ones including matched pairs of proximity characteristic points, the member of which matched pairs of proximity characteristic points is greater than a predetermined rate of a total number of pairs of proximity characteristic points; producing (A8) coordinate matching parameters representing matches between the characteristic points of the first figure and the characteristic points of the second figure with respect to each of the narrowed matched characteristic point pairs; and selectively outputting (A9) the coordinate matching parameters which occur most frequently. The method as defined in claim 1, wherein the amount of relative characteristics contains coordinate values and a direction of the proximity characteristic point in a prescribed coordinate system, the origin of which is determined based on coordinate values of the characteristic point and an orientation of which is determined based on an amount of characteristics of the characteristic point. The method as defined in claim 1 or 2 further comprising the step of: further narrowing down the matched characteristic point pairs, which are already narrowed down, to ones including matched pairs of proximity characteristic points, the member of which matched pairs of proximity characteristic points is greater than a predetermined rate of a total number of pairs of proximity characteristic points therein. The method as defined in claim 1, 2 or 3 further comprising the step of: outputting plural sets of coordinate matching parameters, which include the coordinate matching parameters which occur most frequently. An image matching system comprising: input means for inputting characteristic points of a first figure (11), i.e. configuration, and for inputting characteristic points of a second figure (12); candidate creating means (21) for creating matching characteristic point pair candidates each corresponding to a pair of a first characteristic point, corresponding to one of the characteristic points of the first figure, and a second characteristic point corresponding to one of the characteristic points of the second figure, on the basis of relative characteristics calculated with respect to proximity characteristic points which exist in proximity to the first and second characteristic points respectively; narrowing means (22) or narrowing down the matching characteristic point pair candidates to ones including matched pairs of proximity characteristic points whose differences in relative characteristics do not exceed a prescribed allowable range of error; and parameter producing means (23) for producing coordinate matching parameters representing matches between the characteristic points of the first figure and the characteristic points of the second figure with respect to each of the narrowed matched characteristic point pairs. The system as defined in claim 5 wherein the creating means further comprises decision means for determining whether an amount of relative characteristics calculated for each of proximity characteristic points of the first characteristic point matches the amount of relative characteristics calculated for each of proximity characteristic points of the second characteristic point within a prescribed allowable range of error; and detection means for sequentially detecting pairs of the first and second characteristic points the values, amounts of relative characteristics of which do not exceed the allowable range of error and the number of which is greater than a predetermined number, so that the detected pairs of the first and second characteristic points are used as the matching characteristic point pair candidates. The system as defined in claim 5 or 6 wherein the narrowing means narrows down the matching characteristic point pairs candidates to ones including mathed pairs of proximity characteristic points, the number of which matched pairs of proximity characteristic points is greater than a predetermined rate of a total number of pairs of proximity characteristic points. The system as defined in claim 5, 6 or 12 further comprising output means for selectively outputting the coordinate matching parameters which occur most frequently. The system as defined in claim 5, 6 or 7 further comprising output means for outputting plural sets of the coordinate matching parameters, which include the coordinate matching parameters which occur most frequently. matched pairs of proximity characteristic points rate The system as defined in any one of claims 5 to 9 wherein the first figure corresponds to a search fingerprint while the second figure corresponds to a file fingerprint. The system according to claim 5, wherein said system is adapted to locate a first figure within a second figure by comparing characteristic points of the first figure with characteristic points of the second figure, said system comprising: designation means for designating one of the characteristic points of the first figure as a first characteristic point and for designating one of the characteristic points of the second figure as a second characteristic point relative to the first characteristic point; calculation means for calculating a first amount of relative characteristics for each of proximity characteristic points, which exist in proximity to the first characteristic point, son the basis of a relationship between the first characteristic point and each of the proximity characteristic points, and for calculating a second amount of relative characteristics for each of proximity characteristic points, which exist in proximity to the second characteristic point, on the basis of a relationship between the second characteristic point and each of the proximity characteristic points; decision means for determining whether or not the first amount of relative characteristics matches the second amount of relative characteristics within a prescribed allowable range of error; detection means for sequentially detecting pairs of the first and second characteristic points, the amounts of relative characteristics of which do not exceed the allowable range of error and the number of which is greater than a predetermined number, so that the detected pairs of the first and second characteristic points are used as matching characteristic point pair candidates; narrowing means for narrowing down the matching characteristic point pair candidates to ones including matched pairs of proximity characteristic points, the number of which matched pairs of proximity characteristics points is greater than a predetermined rate of a total number of pairs of proximity characteristic points; parameter producing means for producing coordinate matching parameters representing matches between the characteristic points of the first figure and the characteristic points of the second figure with respect to each of the narrowed matched characteristic point pairs; and output means for selectively outputting the coordinate matching parameters which occur most frequently. The system as defined in claim 11 wherein the amount of relative characteristics contains coordinate values and a direction of the proximity characteristic point in a prescribed coordinate system, the origin of which is determined based on coordinate values of the characteristic point and an orientation of which is determined based on an amount of characteristics of the characteristic point. The system as defined in claim 11 or 12 further comprising: further narrowing means for further narrowing down the matched characteristic point pairs, which an already narrowed down to ones including matched pairs of proximity characteristic points, the number of which matched pairs of proximity characteristic points is greater than a predetermined rate of a total number of pairs of proximity characteristic points therein. The system as defined in claim 11, 12 or 13, wherein the output means outputs plural sets of coordinate matching parameters, which include the coordinate matching parameters which occur most frequently. A machine-readable recording medium storing an image matching program which causes a machine to perform processes comprising the steps of: creating matching characteristic point pair candidates (13) each corresponding to a pair of a first characteristic point, corresponding to one of the characteristic points of a first figure, i.e. configuration, and a second characteristic point corresponding to one of the characteristic points of a second figure, on the basis of relative characteristics calculated for proximity characteristic points narrowing down (16) the matching characteristic point pair candidates to ones including matched pairs of proximity characteristic points whose differences in relative characteristics do not exceed a prescribed allowable range of error; and producing (A8) coordinate matching parameters representing matches between the characteristic points of the first figure with the characteristic points of the second figure with respect to each narrowed matched characteristic point pair. A machine-readable recording medium according to claim 15 storing a program which causes a computer to operate as an image matching device which in adapted to locate a first figure within a second figure by comparing characteristic points of the first figure with characteristic points of the second figure, said program performing processes comprising the steps of: designating one of the characteristic points of the first figure as a first characteristic point; designating one of the characteristic points of the second figure as a second characteristic point relative to the first characteristic point; calculating a first amount of relative characteristics for each of proximity characteristic points, which exist in proximity to the first characteristic point, on the basis of a relationship between the first characteristic point and each of the proximity characteristic points; calculating a second amount of relative characteristics for each of proximity characteristic points, which exist in proximity to the second characteristic point, on the basis of a relationship between the second characteristic point and each of the proximity characteristic points; determining whether or not the first amount of relative characteristics matches the second amount of relative characteristics within a prescribed allowable range of error; sequentially detecting pairs of the first and second characteristic points, the amounts of relative characteristics of which do not exceed the allowable range of error and the number of which is greater than a predetermined number, so that the detected pairs of the first and second characteristic points are used as matching characteristic point pair candidates; narrowing down the matching characteristic point pair candidates to ones including matched pairs of proximity characteristic points, the number of which matched pairs of proximity characteristic points is greater than a predetermined rate of a total number of pairs of proximity characteristic points; producing coordinate matching parameters representing matches between the characteristic points of the first figure and the characteristic points of the second figure with respect to each of the narrowed matched characteristic point pairs; and selectively outputting the coordinate matching parameters which occur most frequently.

Inventors: MONDEN AKIRA, MONDEN, AKIRA
Applicants: NIPPON ELECTRIC CO, NEC CORPORATION
Application year: 1998
Main classification: G06K9
IPC codes: G06K9, G06T7