Abstract:
An image pickup device ( 100 ) wherein a target area, on which an exposure control is based, is accurately detected to perform the exposure control most favorably to the target. The image pickup device ( 100 ) comprises a feature detecting unit ( 111 ) that detects, based on the contour of the target, a target candidate from a picked-up image (S 1 ); a block voting unit ( 112 ) that votes those ones of a plurality of blocks to which the target detected by the feature detecting unit ( 111 ) belong, the plurality of blocks being obtained by dividing the area of the picked-up image into the plurality of blocks; a vote compiling unit ( 114 ) that adds vote results (S 3 ) together on a block-by-block basis over a plurality of frames, thereby compiling the vote results (S 3 ); a significance determining unit ( 115 ) that select, based on a compilation result (S 4 ), blocks to be used for controlling the exposure; and a control unit ( 116 ) that controls the exposure of an image pickup unit ( 101 ) based on the brightness of the blocks selected by the significance determining unit ( 115 ).

Description:
TECHNICAL FIELD 
     The present invention relates to an imaging apparatus and an imaging method. The present invention in particular relates to a method of controlling exposure. The present invention is suitable in use for exposure control when imaging a subject whose brightness changes significantly in the direction of time, such as a vehicle-mounted camera. 
     BACKGROUND ART 
     Conventionally, an imaging apparatus such as a digital still camera is generally provided with an automatic exposure (AE) function for adjusting the amount of exposure automatically. Exposure control is performed by measuring the amount of light in the view, and, based on the measuring result, adjusting the aperture of the lens, the electronic shutter amount, and the gain of electrical signals output from the imaging element. 
     To measure the amount of light, a dedicated sensor or output signals of an imaging element is used. Examples of a method of measuring the amount of light includes the full-screen average metering method by which the average brightness in the whole screen is measured, the center-weighted average metering method by which the brightness at the center part in the screen is selectively measured, the multi-zone metering method by which the screen is divided and the average brightness in each area is measured, the spot metering method by which the brightness at an arbitrary position in the screen is measured, and the multi-spot metering method by which the brightness at a plurality of arbitrary positions in the screen is measured. 
     In spot metering, the part that is desired to be focused on or that needs to be focused on, i.e. the part of high importance, in the screen is detected, and the average brightness in the area is measured. Examples of parts of high importance include a face, a person, and a letter. Further, as for a vehicle-mounted imaging apparatus, examples of parts of high importance include a vehicle traveling on the road, a white line, and a road sign at the roadside. 
     Patent Literature 1 discloses a method of controlling exposure for detecting a white line. In the case where a vehicle is traveling on the road where there are sunlight and shade alternately, hunting occurs if the timing when sunlight and shade switch does not synchronize with the timing of exposure control. To prevent hunting, Patent Literature 1 discloses a technique of providing a limit value for an increase and a limit value for a decrease with respect to the amount of change in exposure control, and limiting the amount of change in exposure control to the limit values when the amount of change exceeds these limit values. 
     Further, Patent Literature 2 discloses a method of controlling the resolution and exposure in an area containing an object of high importance, for example, a vehicle traveling ahead, a person, and a road sign. An area with an object of high importance is determined based on how well the shape of the object in the image matches with the memorized shape of an object, and the camera is controlled so as to set the resolution and the exposure in the area are set at predetermined values. When there are a plurality of areas with an object of high importance, a weight is applied based on the type of an object of high importance (whether it is a person, a vehicle, or a road sign) and the position thereof in the screen (whether it is inside the road or outside the road, or whether it is near or far from the subject vehicle), and determines the exposure using the average result. 
     CITATION LIST 
     Patent Literature 
     
         
         PTL1 
         Japanese Patent Application Laid-Open No. 2005-148309 
         PTL2 
         Japanese Patent Application Laid-Open No. 2008-53901 
       
    
     SUMMARY OF INVENTION 
     Technical Problem 
     By the way, either of the above-described conventional exposure control techniques is an exposure control method based on the area with an object of high importance, and after detecting the area with an object of high importance, exposure control is performed based on the brightness of the detected area. 
     Therefore, it is important to precisely detect the area with an object of high importance, which serves as a basis of exposure control. 
     Patent Literature 1 presumes setting a white line and a road surface area not including the white line. However, in setting a white line, there is a possibility that an error occurs or setting cannot be performed. For example, there is a possibility that the outline of a vehicle compartment of a vehicle traveling ahead is misidentified as a line in the traffic lane (a white line). Further, when highlight is blown out in the entirety of a road surface due to the backlight, there is a possibility that a white line cannot be detected. In these cases, it is difficult to use the exposure control technique according to Patent Literature 1. 
     According to Patent Literature 2, the area with an object of high importance is uniquely identified by the outline shape of the object of high importance. Therefore, when an object having an outline similar to the outline of an object of high importance is contained in a photographed image, there is a possibility of missing the area with an object of high importance. Specifically, exposure control for detecting a road sign will be described as an example below. When imaging a road sign using a vehicle-mounted imaging apparatus, it is common that a plurality of shapes such as triangles and circles are detected from the image. Examples of a plurality of shapes to be detected include, besides road signs, specific parts of buildings around the road and branches of trees. Therefore, there is a possibility that a building around the road or branches of a tree is misidentified for a road sign. As a result of this, incorrect exposure control might be performed where the brightness of an object other than a road sign is optimized regardless of the intention of optimizing the exposure of a road sign. 
     In view of the above, it is therefore an object of the present invention to provide an imaging apparatus and an imaging method for accurately detecting a target area which serves as a basis of exposure control and performing optimal exposure control for the target. 
     Solution to Problem 
     One aspect of an imaging apparatus according to the present invention employs a configuration to have an imaging section that obtains a photographed image; a detection section that detects candidates of a target from the photographed image based on an outline shape of the target; a voting section that, out of a plurality of blocks that are obtained by dividing an area of the photographed image, gives votes to blocks to which the target candidates detected by the detection section belong; a counting section that counts vote results by adding the vote results in each block over a plurality of frames; a determination section that determines importance of each block based on counting results and selects a block to use to control exposure; and a control section that calculates an exposure control parameter to use in the imaging section based on brightness of the block selected by the determination section, and controls exposure in the imaging section. 
     One aspect of an imaging method according to the present invention employs a configuration to have an imaging step that obtains a photographed image; a detection step that detects target candidates from the photographed image based on an outline shape of the target; a voting step that, out of a plurality of blocks that are obtained by dividing an area of the photographed image, gives votes to blocks to which the target candidates detected by the detection step belong; a counting step that counts vote results by adding the vote results in each block over a plurality of frames; a determination step that determines importance of each block based on counting results and selects a block to use to control exposure; and a control step that calculates an exposure control parameter to use in the imaging step based on brightness of the block selected by the determination step, and controls exposure in the imaging step. 
     Advantageous Effects of Invention 
     According to the present invention, by selecting a block for exposure control based on the result of voting in a plurality of frames, even when an object having an outline similar to the outline of a target is contained in one frame of a photographed image, it is possible, without misidentifying that object, to accurately detect a target area which serves as a basis of exposure control, and perform optimal exposure control for the target. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  shows a configuration of an imaging apparatus according to Embodiment 1 of the present invention; 
         FIGS. 2A to 2E  explain voting to each block by a block voting section, and  FIG. 2F  explains counting by a vote counting section; 
         FIG. 3  is a block diagram showing a configuration of an imaging apparatus according to Embodiment 2; 
         FIGS. 4A to 4E  explain voting to each block by a block voting section, and  FIG. 4F  explains counting by a vote counting section; 
         FIG. 5  is a block diagram showing a configuration of an imaging apparatus according to Embodiment 4; 
         FIG. 6  is a block diagram showing a configuration of an analysis section; 
         FIG. 7  is a block diagram showing a configuration of an analysis section; 
         FIGS. 8A to 8F  explain blocks generated by a block generation section; 
         FIG. 9  is a block diagram showing a configuration of an imaging apparatus according to Embodiment 5; 
         FIG. 10  is a block diagram showing a configuration of an imaging apparatus according to Embodiment 6; and 
         FIG. 11  is a block diagram showing a configuration of an imaging apparatus according to Embodiment 7. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Now, embodiments of the present invention will be described in detail with reference to the accompanying drawings. Although cases will be described with the following embodiments where the present invention is applied to road sign recognition, the scope of application of the present invention is by no means limited to road signs. The present invention is applicable in recognizing a wide range of specific objects. The present invention, however, is particularly suitable for the case where a target can be captured stably in almost the same position and the imaging conditions of other objects change over a plurality of frames (for example, 5 to 10 frames) as is the case with a road sign. 
     Embodiment 1 
       FIG. 1  shows a configuration of an imaging apparatus according to Embodiment 1 of the present invention. Imaging apparatus  100  is provided mainly with imaging section  101 , image processing section  102 , output section  103 , and exposure control section  110 . 
     Imaging section  101  obtains an image using an imaging element such as a CCD or a CMOS. As a configuration of imaging section  101 , any known configuration can be used. For example, imaging section  101  is provided with a lens, an aperture control mechanism, a shutter-speed control mechanism, and a focus control mechanism to adjust input light. Further, imaging section  101  is provided with a gain control mechanism such as an amplifier and an A/D converter to adjust the electrical characteristics of the imaging element. Further, imaging section  101  is provided with an I/F for output and a timing generator for coordination in each component. Imaging section  101  sends out photographed image S 1  to image processing section  102  and exposure control section  110 . 
     Here, imaging section  101  controls exposure by performing aperture control, shutter-speed control, and gain control. According to the present invention, however, a configuration and a method for exposure control in imaging section  101  are not limited to particular ones, and it is possible to use various configurations and methods that are suggested conventionally. 
     Image processing section  102  processes photographed image S 1  for a specific purpose. According to the present embodiment, image processing section  102  recognizes a designated object using photographed image  51 . For example, by performing pattern matching processing using a template corresponding to a pre-memorized, designated object and photographed image S 1 , image processing section  102  recognizes whether or not the designated object exists in photographed image S 1  and where the designated object is positioned in photographed image S 1 . Further, image processing section  102  may perform processing of improving the image quality and processing of converting the image size, in addition to processing of recognizing a designated object. The processing result of image processing section  102  is sent out to output section  103 . 
     Output section  103  sends out the recognition result or the image obtained in image processing section  102  to a warning apparatus or a display apparatus. 
     Exposure control section  110  inputs photographed image S 1  to characteristic detection section  111 . Characteristic detection section  111  detects target candidates from photographed image S 1  based on a characteristic of the target. According to the present embodiment, target candidates are detected using an outline shape of the target as a characteristic of the target. Specifically, characteristic detection section  111  detects an object image that coincides with the outline shape of the target from photographed image S 1  by performing processing such as pattern matching, and sends out positional information of the detected object image to block voting section  112  as characteristic information S 2 . In the case of the present embodiment, the target refers to a road sign, and the outline shape of the target refers to a triangle and a circle. 
     Block generation section  113  generates block information to divide an image area of photographed image S 1  into a plurality of blocks, and sends out the generated block information to block voting section  112 . For example, block generation section  113  generates block information to divide a VGA image having a size of 640 pixel×480 pixel into 100 blocks of images each of which having a size of 64 pixel×48 pixel. 
     Block voting section  112 , out of a plurality of blocks generated by block generation section  113   a , gives vote to the block to which the target detected by characteristic detection section  111  belongs. This voting is performed per frame. 
       FIG. 2  shows voting by block voting section  112  and successive counting by vote counting section  114 .  FIG. 2  shows a case where photographed image S 1  is divided into nine blocks to make the figure simpler. 
     As shown in  FIGS. 2A to 2E , block voting section  112  determines which block the outline shape of the target belongs to in the frame at each time point, and gives a vote to the block to which the outline shape belongs. For example, in the frame at the time point (t- 4 ) shown in  FIG. 2A , because the target having a triangular outline shape (a road sign “STOP,” for example) is detected in the middle-left block and the upper-right block, block voting section  112  gives a vote to each of the middle-left block and the upper-right block in the frame at the time point (t- 4 ). Further, for example, in the frame at the time point (t- 2 ) shown in  FIG. 2C , because the target having a triangular outline shape is detected in the middle-left block, block voting section  112  gives a vote to the middle-left block in the frame at the time point (t- 2 ). 
     In this regard, when the detected outline shape straddles across a plurality of neighboring blocks, a vote may be given to the block to which the center point of the detected outline shape belongs. Further, in the same frame, when a plurality of the same outline shapes are detected in the same block (for example, when two triangles are detected in the same block), it is preferable to give only a vote to the block in the frame, without giving a plurality of votes to the block. 
     As described above, block voting section  112  gives a vote to the block to which the outline shape of each target belongs, per frame image. Vote result S 3  of block voting section  112  for each frame is sent out to vote counting section  114 . 
     Vote counting section  114  counts the vote result by adding vote result S 3  in each block over a plurality of frames. As a result of this, vote counting section  114  obtains a counting result shown in  FIG. 2F . The counting result in  FIG. 2F  shows that, for a triangle outline, four votes are given to the middle-left block and two votes are given to the upper-right block. Vote counting section  114  sends out counting result S 4  to importance determination section  115 . Although a case is illustrated in  FIG. 2  as an example where vote counting section  114  counts the vote result over five frames, the number of frames is not limited to five. 
     Importance determination section  115  determines the importance of each block based on counting result S 4 . Specifically, importance determination section  115  determines the block obtaining the largest number of votes (the middle-left block in the case of  FIG. 2F ) as the most important block, and sends out determination result S 5  to control section  116 . 
     Here, when there are a plurality of blocks obtaining the largest number of votes, it is preferable to determine the most important block as described below. 
     Determining a block obtaining larger number of votes in the recent frame over time as a more important block. 
     Determining a block in a more important spatial position as a more important block. For example, when a vehicle travels on the left side and the target is a road sign, because road signs are likely to be positioned at the left side or the upper side in an imaging display, it is preferable to set the block at the left side or the upper side in the imaging display as the important block. 
     Control section  116  controls exposure in imaging section  101  by using the block that is determined as the most important block by importance determination section  115  as the block for exposure control. Specifically, control section  116  controls exposure in imaging section  101  by inputting photographed images S 1  from imaging section  101 , detecting the brightness of the most important block out of photographed images S 1 , calculating camera control parameter S 6  such that the average brightness of the most important block is within the predetermined range of brightness, and sending out camera control parameter S 6  to imaging section  101 . 
     As described above, according to the present embodiment, by providing characteristic detection section  111  that detects target candidates from photographed image S 1  based on the outline shape of the target, block voting section  112  that, out of a plurality of blocks that are obtained by dividing a photographed image area, gives a vote to the block to which the target detected by characteristic detection section  111  belongs, vote counting section  114  that counts vote result S 3  by adding vote results S 3  in each block over a plurality of frames, importance determination section  115  that selects a block to use to control exposure based on counting result S 4 , and control section  116  that controls exposure in imaging section  101  based on the brightness of the block selected by importance determination section  115 , even when an object having an outline similar to the outline shape of the target is contained in one frame of a photographed image, it is possible, without misidentifying that object, to accurately detect a target area which serves as a basis of exposure control, and perform optimal exposure control for the target. 
     As a result of this, image processing section  102  can perform recognition processing using a photographed image in which the brightness of a target is optimized, improving the recognition accuracy. 
     Here, a reason will be described below why the present embodiment is highly effective in traffic sign recognition. 
     (1) Because road signs are mounted such that the display surface faces in the direction of a traveling vehicle, road signs have a uniform reflectivity, compared to other objects to be imaged such as buildings and trees. That is, for road signs, because changes in reflectivity are small even when a vehicle changes the traveling direction and traveling position over time, road signs are likely to be detected stably, compared to other objects such as buildings and trees. That is, traffic signs are robust against changes in a relative direction and the position with respect to imaging apparatus  100 . On the other hand, because the reflectivity of imaging areas such as specific parts of buildings and branches of trees near the road varies per pixel, such imaging areas are unlikely to be detected when the vehicle-mounted imaging apparatus moves and the relative direction changes. 
     (2) Because located in a predetermined position such as at the side or the upper side on the road, road signs are located in almost fixed position in a photographed image, even when a vehicle changes the traveling direction and the traveling position over time, if it is short in time. Therefore, votes tend to concentrate on a certain block, so voting and counting according to the present embodiment are effective. Further, as described above, it is possible to select an optimal block for exposure control, taking the importance of spatial position into account. 
     Embodiment 2 
     A case has been described with Embodiment 1 where a block having the outline shape of the target is determined by voting, and the block obtaining the largest number of votes is selected as the block for exposure control. A case will be described with the present embodiment where, in addition to the above configuration, a block for exposure control is selected taking into account the priority corresponding to the type of the outline shape and the pattern in the outline. 
     Specifically, the following priority is granted. 
     (1) Priority granted according to the type of the outline shape: For example, the priority of a road sign having a triangular outline shape is set higher than the priority of a road sign having a circular outline shape. 
     (2) Priority granted according to the pattern in the outline: For example, when outline shapes are the same triangles, the priority of a road sign “STOP” is set higher than the priority of a road sign “GO SLOW.” Further, when outline shapes are the same circles, the priority of the speed limit sign is set higher than the priority of the no-parking sign. 
     (3) Priority granted according to both the type of the outline shape and the pattern in the outline: For example, when a road sign having a triangular outline shape and a pattern in an outline of “STOP” and a road sign having a circular outline shape and a pattern in an outline of “SPEED LIMIT” are detected, the priority is granted in order of “STOP”&gt;“SPEED LIMIT”&gt;triangle&gt;circle. That is, in determining the importance actually, because sometimes the outline shape alone is not sufficient, with the present embodiment, the pattern in the outline is added as an element of priority, in addition to the type of the outline shape. 
     However, as for an image before exposure control, there is a possibility that a pattern in the outline cannot be detected, the priority of a pattern in the outline may not be granted. 
       FIG. 3  shows a configuration of an imaging apparatus according to the present embodiment, in which the same reference numerals as in  FIG. 1  are used for the parts that are the same as in  FIG. 1 . Exposure control section  201  of imaging apparatus  200  is provided with priority granting section  202 . Further, characteristic detection section  203  according to the present embodiment detects the outline shape and the pattern in the outline as a characteristic of the target. Therefore, characteristic detection section  203  outputs information about the type and the position of the detected outline shape and the type and the position of the pattern in the outline, as characteristic information S 2 . 
     Block voting section  112  gives a vote to a block per type of the detected outline shape and per type of the detected pattern in the outline. Vote counting section  114  counts the number of votes for each block per type of the outline shape and per type of the detected pattern in the outline. 
     Priority granting section  202  grants the priority corresponding to the type of the outline shape and the type of the pattern in the outline to obtained vote (counting) result S 4 . Specifically, priority granting section  202  may apply a weight to obtained vote result S 4  by multiplying a coefficient of a greater value to the type of the outline shape and the pattern in the outline having a higher priority. For example, when granting the priority in order of “STOP”&gt;“SPEED LIMIT”&gt;triangle&gt;circle, priority granting section  202  may multiply the number of votes for “STOP” by a multiplication factor of 2, multiply the number of votes for “SPEED LIMIT” by a multiplication factor of 1.5, multiply the number of votes for a triangle by a multiplication factor of 1, and multiply the number of votes for a circle by a multiplication factor of 0.5. Further, the method of granting priority is not limited to this. For example, it is possible to increase the number of votes at a time for a higher priority in block voting section  112 . 
     New obtained vote (counting) result S 10  which is granted priority as described above is transmitted to importance determination section  115 , and the block obtaining the largest number of votes is selected as the block for exposure control by importance determination section  115 , as is in Embodiment 1. 
       FIG. 4  shows a simple example of an operation when the present embodiment is used.  FIG. 4  shows a vote result and an obtained vote result for a sign having a triangular outline shape and a sign having a circular outline shape. Assume that voting is performed for each frame as shown in  FIGS. 4A to 4E , and the obtained vote result is shown in  FIG. 4F . 
     As is clear from the obtained vote result in  FIG. 4F , the same number of votes is obtained in the upper-left block and the middle-left block. With the present embodiment, however, because the priority of a triangle is set higher than the priority of a circle, the middle-left block is selected as the block for exposure control. 
     According to the present embodiment, in addition to the configuration of Embodiment 1, by granting the priority corresponding to the outline shape of the target or the pattern in the outline of the target, in addition to the effects of Embodiment 1, it is possible to increase the probability of using a target having higher importance as a block for exposure control. 
     Embodiment 3 
     A preferable method of selecting a block for exposure control will be described here with the present embodiment in the case where importance determination section  115  determines that there are a plurality of blocks having the same importance according to the methods presented in Embodiments 1 and 2. 
     Both in the daytime and at the nighttime, it is common that a target candidate in which shadow is blocked up and a target candidate in which highlight is blown out exist in the same frame at the same time depending on the reflecting property of each part and how a light is shined on each part in the image area. For either target, it is possible to detect the outline shape, but it is difficult to confirm the type of the pattern in the outline. As a result of that, there is a possibility that importance determination section  115  determines that there are a plurality of blocks having the same importance. 
     With the present embodiment, which is explained specifically using  FIG. 3 , priority granting section  202  and importance determination section  115  perform an operation that is different from the operation described in Embodiment 2. 
     Importance determination section  115  first performs the operation described in Embodiment 2, and if there are two or more blocks having the same importance, calculates the average brightness of each of such blocks and the average brightness of the whole frame, and compares them. For easier explanation, a case will be described here where there are two blocks having the same importance (the number of votes), that is, block  1  and block  2 . Further, suppose that there is a relationship where the average brightness of block  1  is higher than the average brightness of block  2 . In that case, the following three cases are obtained. 
     (1) Average brightness of block  1 &gt;average brightness of block  2 &gt;average brightness of a frame: In this case, block  2  is selected as the important block, taking into account the fact that a target candidate is likely to be detected when the target candidate is brighter than the whole screen. By this means, because block  1  is maintained to be in a comparatively bright state even when exposure is controlled based on the brightness of block  2 , it is possible to increase the possibility that block  1  can keep being detected. Here, if exposure is controlled based on the brightness of block  1 , exposure will be lowered a lot, decreasing the brightness of block  2  and consequently increasing the possibility that block  2  cannot be detected. 
     (2) Average brightness of a frame&gt;average brightness of block  1 &gt;average brightness of block  2 : In this case, block  1  is selected as an important block, taking into account the fact that a target candidate is likely to be detected when the target candidate is darker than the whole screen. By this means, because block  2  is maintained to be in a comparatively darker state even when exposure is controlled based on the brightness of block  1 , it is possible to increase the possibility that block  2  can keep being detected. Here, if exposure is controlled based on the brightness of block  2 , exposure will be increased a lot, increasing the brightness of block  1  and consequently increasing the possibility that block  1  cannot be detected. 
     (3) Average brightness of block  1 &gt;average brightness of a frame&gt;average brightness of block  2 : In this case, first, the average brightness of the frame is compared with a predetermined brightness (for example, a predetermined brightness value is set at 100 when a range of brightness is from 0 to 255), and when the average brightness of the frame is higher than the predetermined brightness value, block  1  is determined as an important block. If not, block  2  is determined as an important block. The reason is that a dark target candidate detected when the whole screen is bright is considered to be likely in a backlight environment. Even when exposure is controlled based on a bright target candidate, the possibility that a dark target candidate can keep being detected is high. In contrast, when exposure is controlled based on a dark target candidate, the possibility that a bright target candidate will not be detected is high. Further, the possibility is considered to be high that a bright target candidate detected when the whole screen is dark is in the environment to be illuminated by a light, for example. Even when exposure is controlled based on a dark target candidate, the possibility is high that a bright target candidate will can keep being detected. 
     As described above, according to the present embodiment, when determining that there are a plurality of blocks having the same importance, importance determination section  115  selects either block as a block to use to control exposure, out of the plurality of blocks, based on the relationship between the average brightness of each block of the plurality of blocks and the average brightness of the frame. 
     Although a case has been described above where it is determined that there are two blocks having the same importance, it is also possible to apply the same concept as described above to the case where it is determined that there are three or more blocks having the same importance. In short, by selecting a block having the average brightness that is the closest to the average brightness of the frame, out of a plurality of blocks having the same importance, it is possible to keep detecting the remaining blocks. 
     According to the present embodiment, control section  116  controls exposure in imaging section  101  based on the brightness of the block selected by importance determination section  115  as described above. Then, importance determination section  115  excludes the previously-selected block, and selects a new block to use for exposure control based on a new counting result. Then, control section  116  controls exposure in imaging section  101  based on the brightness of the new block selected by importance determination section  115 . Regarding the specific method of excluding the previously-selected block, for example, priority granting section  202  may give a minus vote to the block previously selected by priority granting section  202 . That is, for a block for which the type of the pattern in the outline is confirmed, the importance of the block is lowered by a predetermined value at the time point when the confirmation result is obtained. 
     By this means, it is possible to confirm the pattern in the outline sequentially for all of a plurality of blocks having the same importance without exception. 
     Further, the above-described average brightness of a block may be the average brightness of the whole block or the average brightness of the target candidate that belongs to the block. That is, it is acceptable as long as it is the average brightness within a block. Further, the average brightness of a frame may be the average brightness of a whole screen or the average brightness of related blocks and the average brightness of neighboring blocks. 
     Embodiment 4 
       FIG. 5  shows a configuration of imaging apparatus  500  according to Embodiment 4. Imaging apparatus  500  differs from imaging apparatus  100  of Embodiment 1 in the configuration of exposure control section  501 . Exposure control section  501  comprises block generation section  503  that is configured differently from block generation section  113  ( FIG. 1 ), and analysis section  502 . 
     Imaging apparatus  500  according to Embodiment 4 of the present invention will be described below. In  FIG. 5 , parts that are the same as in  FIG. 1  will be assigned the same reference numerals as in  FIG. 1 . 
     Analysis section  502  analyzes the traveling condition of a vehicle on which imaging apparatus  500  is mounted. Analysis section  502  analyzes, for example, the condition where a vehicle is making a curve turn, the condition where a vehicle is traveling downhill, and the condition where a vehicle is accelerating. Analysis section  502  outputs analysis information showing an analysis result of vehicle&#39;s traveling condition to block generation section  503 . 
       FIG. 6  shows an example of a configuration of analysis section  502 . Analysis section  502  is provided with sensor section  601  and analysis information generation section  602 . Sensor section  601  is an acceleration sensor and a yaw rate sensor, for example. Sensor section  601  senses, for example, the condition where a vehicle is making a curve turn, the condition where a vehicle is traveling downhill, and the condition where a vehicle is accelerating, and reports to analysis information generation section  602 . Upon receiving the report, analysis information generation section  602  generates and outputs analysis information. 
     Further, more preferably, analysis information includes information about the degree of a curve and acceleration, besides the information about the condition where a vehicle is making a curve turn, the condition where a vehicle is traveling downhill, and the condition where a vehicle is accelerating. 
       FIG. 7  shows yet another example of a configuration of analysis section  502 . Analysis section  502  is provided with global positioning system (GPS) reception section  701 , storage section  702  that stores map information, and analysis information generation section  703 . GPS reception section  701  obtains the position of a vehicle and outputs positional information to analysis information generation section  703 . Storage section  702  outputs map information to analysis information generation section  703 . Analysis information generation section  703  analyzes a vehicle&#39;s traveling condition based on the positional information and the map information, and generates and outputs analysis information. That is, the analysis information includes positional information of a vehicle in a map. 
     Further,  FIGS. 6 and 7  shows merely examples of a configuration of the analysis section, and the analysis section may be any configuration as long as the analysis section has a function of analyzing a vehicle&#39;s traveling condition. 
     Block generation section  503  inputs the analysis information from analysis section  502 . Block generation section  503  generates block information based on the analysis information. That is, block generation section  503  generates block information based on the vehicle&#39;s traveling condition. For example, block generation section  503  changes block information depending on whether a vehicle is in the condition of making a right curve turn or a vehicle is in the condition of making a left curve turn, and outputs the block information to block voting section  112 . 
       FIG. 8  shows photographed images each of which is split into a plurality of blocks using block information generated by block generation section  503  based on the analysis information. Block generation section  503  will be described below using  FIG. 8 . 
       FIG. 8A  shows a photographed image when analysis information indicates that a vehicle is making a right curve turn. When a vehicle is making a right curve turn, changes are greater in the left part of an image than in the right part of the image in the photographed image. Therefore, blocks in the left part are made larger than blocks in the right part. As described above, according to the present embodiment, a block is made larger for the area in which an image changes greater. 
     The reason of doing this will be described below in short. As changes in an image are greater, the accuracy of detection by characteristic detection section  111  is lowered, and even when the target exists in the image, the possibility of detecting the target decreases. As a result of this, inconvenience arises that the number of votes by block voting section  112  lowers in an area in which an image changes greater. Therefore, according to the present embodiment, by making a block larger for an area in which an image changes greater, it is possible to increase the number of votes to be given to the area in which the image changes greater. That is, by making a block larger, it is possible to compensate for decrease in the probability of detection. By this means, it is possible to resolve an imbalance in voting to each block caused by the difference in the amount of change in an image, and realize fair voting. 
       FIG. 8B  shows a photographed image when analysis information indicates that a vehicle is making a left curve turn. The principle is the same as described for  FIG. 8A . 
       FIG. 8C  shows a photographed image when analysis information indicates that a vehicle is traveling uphill. When a vehicle is traveling uphill, changes are greater in the lower part of an image than in the upper part of the image in the photographed image. Therefore, blocks in the lower part are made larger than blocks in the upper part in the photographed image. 
       FIG. 8D  shows a photographed image when analysis information indicates that a vehicle is traveling downhill. The principle is the same as described for  FIG. 8C . 
     Block generation section  503  generates information about a block division shown in  FIGS. 8E and 8F  depending on other condition of the speed or acceleration of a vehicle. 
       FIG. 8E  shows a block division when analysis information indicates that the speed or acceleration of a vehicle is equal to or greater than a predetermined threshold value.  FIG. 8F  shows a block division when analysis information indicates that the speed or acceleration of a vehicle is smaller than a predetermined threshold value. When the speed or acceleration of a vehicle is greater, changes are greater at left and right sides of an image than at the center of the image in the photographed image. Therefore, when the speed or acceleration of a vehicle is greater, blocks at left and right sides are made larger than the blocks at the center in the photographed image. 
     Further, an operation of block voting section  112  is the same as described in Embodiment 1, and therefore explanations will be omitted. Further, other operations are the same as described in Embodiment 1, and therefore explanations will be omitted. 
     According to the above configuration, by analyzing vehicle&#39;s traveling condition and changing the size of blocks based on analysis information, it is possible to resolve an imbalance in voting accompanying the traveling condition and accurately detect the target area which serves as a basis of exposure control. 
     Embodiment 5 
       FIG. 9  shows a configuration of imaging apparatus  900  according to Embodiment 5. Imaging apparatus  900  differs from Embodiment 5 in that analysis section  902  of exposure control section  901  outputs photographed image S 1  in imaging section  101 . 
     Imaging apparatus  900  according to Embodiment 5 of the present invention will be described below. In  FIG. 9 , parts that are the same as in  FIG. 5  will be assigned the same reference numerals as in  FIG. 5 . 
     Analysis section  902  receives as input an image obtained by imaging section  101  and performs an image analysis. Analysis section  902  analyzes the traveling condition of a vehicle on which imaging apparatus  900  is mounted by performing an image analysis. Analysis section  902  analyzes, for example, the condition where a vehicle is making a curve turn, the condition where a vehicle is traveling downhill, and the condition where a vehicle is accelerating. That is, analysis section  902  performs the same analysis as in analysis section  502  of Embodiment 4 using a photographed image. As a result of analyzing vehicle&#39;s traveling condition, analysis section  902  outputs analysis information to block generation section  503 . 
     Functions of block generation section  503  are the same as described in Embodiment 4, and therefore explanations will be omitted. 
     According to the above-described configuration, as is the case with Embodiment 4, by analyzing vehicle&#39;s traveling condition and changing the size of blocks based on analysis information, it is possible to resolve an imbalance in voting accompanying the traveling condition and accurately detect a target area which serves as a basis of exposure control. 
     Embodiment 6 
       FIG. 10  shows a configuration of imaging apparatus  1000  according to Embodiment 6. Imaging apparatus  1000  is provided with a configuration, in which importance determination section  115  described in Embodiment 2 and analysis section  502  described in Embodiment 4, are added to the configuration according to Embodiment 1 ( FIG. 1 ). 
     According to the configuration in  FIG. 10 , in addition to the effects of Embodiment 1, it is possible to achieve the effect of increasing the probability of using the target having higher importance as a block for exposure control (the effect of Embodiment 2) and the effect of resolving an imbalance in voting accompanying the traveling condition and accurately detecting the target area which serves as a basis of exposure control (the effect of Embodiment 4). 
     Embodiment 7 
       FIG. 11  shows imaging apparatus  1100  according to Embodiment 7. Imaging apparatus  1100  differs from Embodiment 6 in that analysis section  902  of exposure control section  1101  inputs photographed image S 1  in imaging section  101 . Functions of analysis section  902  are the same as described in Embodiment 5, and therefore explanations will be omitted. 
     According to the configuration in  FIG. 11 , it is possible to achieve the same effects as for the configuration in  FIG. 10 . 
     The disclosure of Japanese Patent Application No. 2009-005929, filed on Jan. 14, 2009, including the specification, drawings and abstract, is incorporated herein by reference in its entirety. 
     INDUSTRIAL APPLICABILITY 
     The present invention has effects of accurately detecting a target area which serves as a basis of exposure control and performing optimal exposure control for the target, and is suitable in use for a vehicle-mounted imaging apparatus that recognizes road signs, for example.