Image processing device, image processing method, and program

Abstract

The objective is to provide a process for obtaining appropriate evaluation results even when evaluating the surface of an object while moving at least one of the object being evaluated or the imaging device. [Solution] The image processing device derives an evaluation confidence level based on the evaluation conditions for evaluating the object surface, and displays a warning regarding the evaluation conditions if the derived evaluation confidence level is below a standard value.

Description

Technical Field

[0001] The present invention relates to a technique for evaluating the surface of an object.

Background Art

[0002] When painting industrial products, the painting material may remain granular on the surface of the product or may not be painted with a uniform thickness, resulting in painting defects. For example, poor smoothness of the painted surface is called orange peel and is a factor in the deterioration of design quality. Patent Document 1 discloses a technique for evaluating the texture of an object based on an image obtained by imaging an object on which a two-dimensional pattern is projected.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When evaluating the surface of an object while moving at least one of the object to be evaluated and the imaging device, there is a problem that an evaluation result different from the evaluation result when the object to be evaluated and the imaging device are stationary is obtained.

[0005] Therefore, an object of the present invention is to provide a process for obtaining an appropriate evaluation result even when evaluating the surface of an object while moving at least one of the object to be evaluated and the imaging device.

Means for Solving the Problems

[0006] To solve the above problems, the image processing apparatus according to the present invention is characterized by having a derivation means for deriving an evaluation reliability based on evaluation conditions in the evaluation of an object surface, and a display control means for displaying a warning regarding the evaluation conditions when the derived evaluation reliability is less than a reference value. [Effects of the Invention]

[0007] According to the present invention, appropriate evaluation results can be obtained even when evaluating the surface of an object while moving at least one of the object to be evaluated and the imaging device. [Brief explanation of the drawing]

[0008] [Figure 1] Diagram showing the configuration of the evaluation system [Figure 2] Diagram showing the functional configuration of the image processing device. [Figure 3] A flowchart showing the processes performed by the image processing unit. [Figure 4] Diagram showing an example of a user interface [Figure 5] A flowchart showing the process for deriving the evaluation confidence level. [Figure 6] A diagram to explain the reliability of the evaluation. [Figure 7] Diagram showing an example of a user interface [Figure 8] Diagram showing an example of a user interface [Figure 9] Flowchart showing the evaluation process [Figure 10] A flowchart showing the process for calculating the "yuzu skin" evaluation value. [Figure 11] A flowchart showing the process for deriving the evaluation confidence level. [Figure 12] A diagram to explain the reliability of the evaluation. [Figure 13] A flowchart showing the processes performed by the image processing unit. [Figure 14] Diagram showing an example of a user interface [Figure 15] A diagram illustrating how to set imaging conditions. [Figure 16] Figure showing an example of a user interface

Best Mode for Carrying Out the Invention

[0009] Hereinafter, each embodiment will be described with reference to the drawings. Note that the following embodiments do not necessarily limit the present invention. Also, not all combinations of features described in each embodiment are essential for the solution means of the present invention.

[0010] [First Embodiment] <Configuration of Evaluation System> FIG. 1(a) is a diagram showing a configuration example of an evaluation system including an image processing apparatus 101 in the present embodiment. The evaluation system includes an image processing apparatus 101, a lighting apparatus 102, and an imaging apparatus 103. The image processing apparatus 101 is connected to the lighting apparatus 102, the imaging apparatus 103, and a driving apparatus 104. The lighting apparatus 102 in the present embodiment is a liquid crystal display and can irradiate a target object with a light and dark pattern having light and dark portions. Note that the lighting apparatus 102 is not limited to a liquid crystal display as long as it is a device that can irradiate a target object with a light and dark pattern having at least a pair of light and dark portions, and may be, for example, a fluorescent lamp or an LED. The imaging apparatus 103 is a CCD camera or a CMOS camera. Note that the imaging apparatus 103 may be a camera that generates a monochrome image or a camera that generates a color image. The driving apparatus 104 is a device that moves the lighting apparatus 102 and the imaging apparatus 103 in a straight line at a constant speed by motor driving. Note that the driving apparatus 104 may drive the object 105 to be evaluated instead of driving the lighting apparatus 102 and the imaging apparatus 103. Also, the driving apparatus 104 may be configured to be able to change the moving speeds of the lighting apparatus 102 and the imaging apparatus 103.

[0011] The image processing device 101 controls the brightness of the lighting device 102 and the shape of the bright area. Further, the image processing device 101 controls the exposure, focus, and imaging timing of the imaging device 103. In the example of Fig. 1(a), the shape of the bright area is stripe-shaped, but it may be other shapes such as linear. The lighting device 102 irradiates light from the light sources it has onto the evaluation surface of the object 105. The object 105 is a part of an industrial product such as a household appliance, and the evaluation surface is a painted surface with specular gloss. The imaging device 103 images the evaluation surface irradiated with light. The image processing device 101 quantifies the degree of orange peel as an evaluation of the surface state of the evaluation surface based on the captured image obtained by imaging.

[0012] Fig. 1(b) is a diagram showing an example of the hardware configuration of the image processing device 101 in the present embodiment. The image processing device 101 is realized by, for example, a PC (personal computer) or the like, and includes a RAM 106, a CPU 107, a ROM 108, and an interface 109. The CPU 107 controls each component via an internal bus 110. The processes described in the flowchart to be described later are stored in the ROM 108 as program codes. These program codes are expanded in the RAM 106 and executed by the CPU 107. A display 112, a mouse 113, and a keyboard 114 are connected to the interface 109 via an external bus 111. The display 112 presents information to the user, and the mouse 113 and the keyboard 114 receive inputs from the user. The lighting device 102, the imaging device 103, and the drive device 104 are also connected to the image processing device 101 via the external bus 111. Incidentally, the display 112 may be a touch panel display having a function of detecting the position of a touch by an indicator such as a finger.

[0013] <Functional Configuration of Image Processing Device> Figure 2 is a block diagram showing the functional configuration of the image processing device 101. The CPU 107 functions as shown in Figure 2 by reading and executing programs stored in the ROM 108 using the RAM 106 as work memory. Note that not all of the following processes need to be executed by the CPU 107; the image processing device 101 may be configured so that some or all of the processes are performed by one or more processing circuits other than the CPU 107.

[0014] The image processing device 101 includes an evaluation condition setting unit 201, a drive control unit 202, an image acquisition unit 203, an evaluation value calculation unit 204, and a display control unit 205. The evaluation condition setting unit 201 sets the brightness of the lighting device 102, the exposure of the imaging device 103, and the speed of the drive device 104. The drive control unit 202 moves the lighting device 102 and the imaging device 103 based on the evaluation conditions. The image acquisition unit 203 acquires image data obtained by imaging the object 105. The evaluation value calculation unit 204 acquires a brightness profile representing the attributes of the area where the lighting is reflected in the image represented by the acquired image data, and calculates an orange peel evaluation value. The display control unit 205 controls the display 112 to present the evaluation condition setting screen to the user.

[0015] <Processing performed by the image processing unit> Figure 3 is a flowchart showing the process performed by the image processing device 101 in this embodiment. Figure 4 is a user interface (UI) screen displayed for setting evaluation conditions in this embodiment. The process shown in the flowchart of Figure 3 is started when the user inputs information into each item on the setting screen 401 via the mouse 113 or keyboard 114 and presses the evaluation start button 406. The drive condition area 402 is an area for setting the drive device 104, and it is possible to set the scanning speed and scanning range of the drive device 104. The imaging condition area 403 is an area for setting the imaging device 103, and it is possible to set the shutter speed, ISO sensitivity, F-number, imaging interval (FPS), and lens focal length. The illumination condition area 404 is an area for setting the illumination device 102, and it is possible to set the brightness of the light source of the illumination device. The calculation condition area 405 is an area for setting the evaluation cycle for orange peel texture. Multiple evaluation cycles can be set, and orange peel texture corresponding to cycles within the range from the lower limit to the upper limit entered by the user can be set as the evaluation target. In this embodiment, the user inputs the setting values ​​on the setting screen 401, but a selection-type input method using a drop-down list or the like may also be used. Alternatively, instead of the user inputting information, the system may read the information set in the illumination device 102, imaging device 103, and drive device 104 and reflect it in the setting of the evaluation conditions. The exit button 407 is a button for ending the process. Hereafter, each step (process) will be represented by adding an S before the symbol.

[0016] In S301, the evaluation condition setting unit 201 acquires setting values ​​corresponding to the drive condition area 402, the imaging condition area 403, and the illumination condition area 404, respectively. In S302, the evaluation condition setting unit 201 acquires the setting value for the orange peel skin evaluation cycle corresponding to the calculation condition area 405. Note that the processing in S301 and S302 may be performed in parallel, or the processing in S302 may be performed first.

[0017] In S303, the evaluation condition setting unit 201 derives the evaluation reliability. In this embodiment, the evaluation condition setting unit 201 derives the evaluation reliability using the relationship that the evaluation reliability decreases due to the effect of subject blur during imaging. Subject blur occurs when the relative position between the imaging device 103 and the object to be evaluated 105 shifts during imaging exposure. The details of the evaluation reliability derivation process in S303 will be explained using the flowchart in Figure 5.

[0018] In S501, the evaluation condition setting unit 201 derives the evaluation reliability based on the amount of subject blur. The amount of subject blur is the relative movement of the subject during the exposure time of the imaging device 103. First, the evaluation condition setting unit 201 calculates the amount of subject blur by multiplying the shutter speed and the scanning speed. Next, the evaluation condition setting unit 201 derives the evaluation reliability based on the relationship between the amount of subject blur and the evaluation reliability. The relationship between the amount of subject blur and the evaluation reliability is shown in Figure 6. The evaluation period A is set to a lower limit of 0.1 mm and an upper limit of 0.3 mm, and the evaluation period D is set to a lower limit of 3.0 mm and an upper limit of 10.0 mm. The evaluation reliability is assumed to decrease monotonically such that it becomes 0 when the amount of subject blur is greater than or equal to the lower limit period. In other words, orange peel, which is high frequency as in evaluation period A, is strongly affected by the amount of subject blur, while orange peel, which is low frequency as in evaluation period D, tends to be less affected by the amount of subject blur. When the shutter speed is 1 / 100 second and the scanning speed is 100 mm / second, the amount of subject blur is 1.0 mm, the evaluation reliability for evaluation period A is 0.05, and the evaluation reliability for evaluation period D is 0.66. Note that the data representing the relationship between the amount of subject blur and the evaluation reliability can be in any format; for example, it may be a lookup table stored in ROM108 that can be referenced. Alternatively, the evaluation reliability may be obtained by referring to data representing the relationship between shutter speed, scanning speed, and evaluation reliability without calculating the amount of subject blur.

[0019] In S502, the evaluation condition setting unit 201 corrects the evaluation reliability based on the resolution and field of view of the captured image. First, the evaluation condition setting unit 201 calculates the real spatial resolution and real spatial field of view of the captured image based on the distance from the object to be evaluated 105 to the imaging device 103, the lens focal length of the imaging device 103, and the sensor size of the imaging device 103. Next, the evaluation condition setting unit 201 determines whether the real spatial resolution of the captured image satisfies the Nyquist frequency with respect to the evaluation period of orange peel. If the Nyquist frequency is not met, the evaluation reliability is set to 0. Next, the evaluation condition setting unit 201 determines whether the real spatial field of view of the captured image is at least a predetermined multiple of the evaluation period of orange peel. In this embodiment, four times the evaluation period is used as the threshold, and if it is less than the threshold, it is considered that the number of samples is insufficient, and the evaluation reliability is set to 0.

[0020] In S503, the evaluation condition setting unit 201 determines whether or not it has derived evaluation reliability for all evaluation cycles set in the calculation condition area 405. If the derivation of all evaluation reliability has been completed, it terminates the process in S303 and proceeds to the process in S304. If the derivation of all evaluation reliability has not been completed, it returns to S501 and derives the evaluation reliability for the evaluation cycles for which the derivation has not been completed.

[0021] In S304, the evaluation condition setting unit 201 determines whether the evaluation reliability of each evaluation period is equal to or greater than the reference value. In this embodiment, the reference value is 0.50. If the evaluation reliability of all evaluation periods is equal to or greater than the reference value, the process proceeds to S306; if the evaluation reliability of any one evaluation period is less than the reference value, the process proceeds to S305.

[0022] In S305, the display control unit 205 displays a warning screen on the display 112 indicating that the evaluation reliability is low. The warning screen in this embodiment is shown in Figure 7. The user is notified of the evaluation cycle in which the evaluation reliability is below the standard value. If the user wants to start the evaluation even though the evaluation reliability is low, they press the evaluation continuation button 701 using the mouse 113. If the user wants to modify the evaluation conditions, they press the evaluation cancellation button 702 using the mouse 113 to cancel the process.

[0023] In S306, the display control unit 205 displays a start confirmation screen on the display 112. The start confirmation screen in this embodiment is shown in Figure 8. The start confirmation screen displays estimated evaluation information, including estimated evaluation time, estimated evaluation interval, and estimated evaluation score. The estimated evaluation time is calculated based on the scanning range and scanning speed of the drive condition area 402. The estimated evaluation interval is calculated based on the scanning speed of the drive condition area 402 and the imaging interval of the imaging condition area 403. The estimated evaluation score is calculated based on the scanning range and scanning speed of the drive condition area 402 and the imaging interval of the imaging condition 403. Note that the information displayed on the start confirmation screen is not limited to the above example. The user presses the evaluation start button 801 using the mouse 113 to start the evaluation, and presses the evaluation cancel button 802 using the mouse 113 to cancel the evaluation.

[0024] In S307, the evaluation value calculation unit 204 calculates the orange peel evaluation value based on the image data obtained by imaging the object 105. The details of the calculation process for the orange peel evaluation value in S307 will be explained using the flowchart in Figure 9. In S901, the drive control unit 202 moves the illumination device 102 and the imaging device 103 at a constant speed at the scanning speed set in the drive condition region 402. In S902, it is determined whether or not the scan has exceeded the scanning range set in the drive condition region 402. If the scan has exceeded the scanning range, the process proceeds to S905; otherwise, the process proceeds to S903.

[0025] In S903, the image acquisition unit 203 controls the illumination device 102 to irradiate the object 105 to be evaluated with a line of light having a uniform width. It also controls the imaging device 103 to image the object 105 to be evaluated, thereby acquiring image data. The captured image data reflects the bright area of ​​the illumination device 102. In S904, the evaluation value calculation unit 204 calculates the evaluation value for orange peel skin based on the captured image. The details of the calculation process for orange peel skin evaluation value in S904 will be explained using the flowchart in Figure 10.

[0026] In S1001, the evaluation value calculation unit 204 obtains luminance values ​​near the center in the short direction for each position in the long direction of the bright region in the captured image where the light source is reflected, and generates a luminance profile based on the obtained luminance values. In this embodiment, the luminance profile is generated using luminance values ​​near the center in the short direction, but it is not limited to the center as long as luminance values ​​at the same relative position with respect to the width of the bright region in the short direction of the bright region can be used. For example, the luminance profile may be generated using luminance values ​​near the edge of the light source reflection region where the degree to which the orange peel texture is visible becomes more pronounced.

[0027] In S1002, the evaluation value calculation unit 204 performs a window function process on the luminance profile and calculates the power spectrum based on the luminance profile after the window function process. A known Hann window is used as the window function, but other window functions may also be used. The evaluation value calculation unit 204 performs a known Fourier transform process on the luminance profile after the window function process and calculates the power spectrum by squaring the amplitude component. In addition, the real-space resolution of the captured image for calculating the period corresponding to the power spectrum is calculated based on the distance from the object 105 to be evaluated to the imaging device 103, the lens focal length of the imaging device 103, and the sensor size of the imaging device 103.

[0028] In S1003, the evaluation value calculation unit 204 integrates the calculated power spectrum over a predetermined period range, and then calculates the square root of the integrated value as the evaluation value.

[0029]

number

[0030] Here, W is the orange peel evaluation value, P is the power spectrum, f1 is the lower limit of the integration interval, f2 is the upper limit of the integration interval, and Δf is the frequency step size. The evaluation value calculation unit 204 calculates the orange peel evaluation value for each evaluation cycle in the calculation condition region 405.

[0031] In S905, the drive control unit 202 terminates the constant-velocity movement of the illumination device 102 and the imaging device 103. At this time, it may also perform an operation to return to the drive origin. In S308, the display control unit 205 displays the orange peel evaluation value as the evaluation result on the display 112. The evaluation value calculation unit 204 also stores the evaluation conditions and the evaluation values ​​at each evaluation position in the ROM 108.

[0032] As described above, in this embodiment, when performing orange peel evaluation by taking images while moving at least one of the object to be evaluated 105 and the imaging device 103, the image processing device 101 derives an evaluation reliability score corresponding to subject blur for each evaluation cycle. If the derived evaluation reliability score is below a standard value, a warning screen is displayed to the user. This prevents situations where an orange peel evaluation value equivalent to that of a stationary state cannot be obtained due to the setting of inappropriate evaluation conditions.

[0033] <Variation> In this embodiment, the degree of orange peel texture was evaluated, but it may also be a visual inspection that detects defects on the object surface, such as scratches and blemishes, from the light source reflection area of ​​the captured image. If a localized defect is included in the light source reflection area, the brightness at that location in the brightness profile will show a dark value. The size of the defect to be detected is set in the calculation condition area 405, and if the length of the relatively dark continuous area in the brightness profile is greater than a predetermined size, the dark continuous area is detected as a defect.

[0034] [Second Embodiment] To mitigate the effects of motion blur, lowering the exposure of the imaging device 103 or increasing the shutter speed to capture images in a darker setting may increase the noise in the captured image, potentially reducing the reliability of the evaluation. In this embodiment, the reliability of the evaluation is derived by also considering the effects of noise contained in the captured image. The hardware and functional configurations of the image processing device 101 in this embodiment are the same as those of the first embodiment, so their description is omitted. The following mainly describes the differences between this embodiment and the first embodiment. Components identical to those in the first embodiment are denoted by the same reference numerals.

[0035] <Processing performed by the image processing unit> In S303, the evaluation condition setting unit 201 derives the evaluation reliability. In this embodiment, the evaluation condition setting unit 201 derives the evaluation reliability by using the relationship that the evaluation reliability decreases due to the effects of subject blur during imaging and noise in the captured image. The details of the evaluation reliability derivation process in S303 will be explained using the flowchart in Figure 11. Note that the processes in S501, S502, and S503 are the same as in the first embodiment, so their explanation will be omitted.

[0036] In S1101, the evaluation condition setting unit 201 derives the evaluation reliability based on information correlated with the amount of noise in the captured image. The information correlated with the amount of noise in the captured image is the ISO sensitivity of the imaging device 103, the shutter speed of the imaging device 103, and the brightness of the light source of the illumination device 102. Figure 12 shows the relationship between each condition and the amount of noise in the captured image. The evaluation period A is set to a lower limit of 0.1 mm and an upper limit of 0.3 mm, and the evaluation period D is set to a lower limit of 3.0 mm and an upper limit of 10.0 mm. Regarding ISO sensitivity, the higher the ISO sensitivity, the more noise there is in the captured image. Therefore, the evaluation reliability is set to decrease monotonically with increasing ISO sensitivity. Regarding shutter speed and light source brightness, the higher the shutter speed and the lower the light source brightness, the lower the imaging exposure. Since a lower imaging exposure results in lower contrast in the captured image, there is relatively more noise. Therefore, the evaluation reliability is set to increase monotonically with increasing imaging exposure. In this embodiment, imaging exposure is expressed by equation (2) based on the known APEX relation.

[0037]

number

[0038] Here, I is the image exposure, BV is the luminance index, TV is the exposure time index, B is the light source luminance, T is the shutter speed, N is the conversion factor of 0.32, and K is the calibration constant of the reflected light exposure meter of 12.5.

[0039] In high-frequency orange peel textures like evaluation period A, the image is strongly affected by noise, while in low-frequency orange peel textures like evaluation period D, the image tends to be less affected by noise. At an ISO sensitivity of 200, the evaluation confidence for evaluation period A is 0.90, and for evaluation period D it is 0.95. (Also, shutter speed 1 / 100 second, light source brightness 10000 cd / m²) 2 In this case, the evaluation confidence for evaluation period A is 0.80, and the evaluation confidence for evaluation period D is 0.90. Note that the data representing the relationship between ISO sensitivity and evaluation confidence, and the relationship between imaging exposure and evaluation confidence, can be in any format; for example, it may refer to data stored in ROM108 as a lookup table.

[0040] In S1102, the evaluation condition setting unit 201 multiplies the evaluation reliability for subject blur and the evaluation reliability for noise in the captured image for each evaluation cycle to derive an evaluation reliability that takes into account both subject blur and noise in the captured image. The evaluation reliability for evaluation cycle A is 0.05 × 0.90 × 0.80 = 0.04. The evaluation reliability for evaluation cycle D is 0.66 × 0.95 × 0.90 = 0.56.

[0041] As described above, the image processing device 101 in this embodiment derives an evaluation reliability score that takes into account subject blur and noise in the captured image, and displays a warning screen to the user if the evaluation reliability score is below a standard value. This prevents the inability to obtain an orange peel evaluation value equivalent to that of a stationary state due to the setting of inappropriate evaluation conditions.

[0042] <Variation> In this embodiment, the evaluation reliability was derived considering both subject blur and noise in the captured image. However, it is also possible to derive the evaluation reliability considering only the noise in the captured image without considering subject blur. In this case, in S303, the processes in S1101, S502, and S503 should be performed without performing the processes in S501 and S1102.

[0043] [Third Embodiment] In this embodiment, imaging conditions are automatically set based on the evaluation reliability. The hardware and functional configurations of the image processing device 101 in this embodiment are the same as those of the first embodiment, and therefore, their description is omitted. The following will mainly describe the differences between this embodiment and the first embodiment. Components identical to those in the first embodiment will be denoted by the same reference numerals.

[0044] <Processing performed by the image processing unit> Figure 13 is a flowchart showing the processes performed by the image processing device 101 in this embodiment. Figure 14 is a UI screen displayed for setting evaluation conditions in this embodiment. When the user presses the automatic setting checkbox 1401 with the mouse 113, the shutter speed and ISO sensitivity in the imaging condition area 403 become uninputtable, and the shutter speed and ISO sensitivity are automatically set according to the other setting items. Note that the processes in S301, S302, S307, and S308 are the same as in the first embodiment, so their explanation is omitted.

[0045] In S1301, the evaluation condition setting unit 201 derives imaging conditions based on evaluation reliability. First, for each combination of shutter speed and ISO sensitivity that can be set as imaging conditions, the evaluation condition setting unit 201 derives evaluation reliability corresponding to subject blur and evaluation reliability corresponding to noise in the captured image, and multiplies the derived evaluation reliability. Scanning speed 100 mm / sec, shutter speed 1 / 100 sec, ISO sensitivity 200, light source brightness 10000 cd / m 2Figure 15 shows the evaluation reliability for evaluation cycle D in this case. The evaluation condition setting unit 201 sets the imaging conditions to the combination of shutter speed and ISO sensitivity that results in an evaluation reliability equal to or greater than the reference value and the highest evaluation reliability. In the example in Figure 15, the evaluation condition setting unit 201 sets the shutter speed to 1 / 200 second and the ISO sensitivity to 200. Note that if multiple evaluation cycles are set, the imaging conditions that result in the highest evaluation reliability may differ. In that case, the imaging conditions are set to the condition that results in an evaluation reliability equal to or greater than the reference value and the sum of the evaluation reliability values ​​for each evaluation cycle is highest. Furthermore, if the evaluation reliability cannot be satisfied with being equal to or greater than the reference value in all evaluation cycles, the scanning speed of the drive unit 104 is slowed down to derive the imaging conditions.

[0046] In S1302, the display control unit 205 displays a start confirmation screen on the display 112. The start confirmation screen in this embodiment is shown in Figure 16. The start confirmation screen displays the shutter speed and ISO sensitivity as automatically set imaging conditions. In addition, if the evaluation reliability does not meet the standard value in all evaluation cycles and the scanning speed of the drive unit 104 is changed, the changed scanning speed is also displayed. Furthermore, estimated evaluation information such as estimated evaluation time, estimated evaluation interval, and estimated evaluation score is displayed. Note that the information displayed on the start confirmation screen is not limited to the above example. The user presses the evaluation start button 1601 using the mouse 113 to start the evaluation, and presses the evaluation cancel button 1602 using the mouse 113 to cancel the evaluation.

[0047] As described above, the image processing device 101 in this embodiment automatically sets the imaging conditions based on the evaluation reliability. This prevents the failure to obtain an orange peel evaluation value equivalent to that of a static state due to the setting of inappropriate evaluation conditions.

[0048] <Variation> In this embodiment, evaluation reliability was derived for each combination of shutter speed and ISO sensitivity that can be set as imaging conditions. However, the combinations of imaging conditions for which evaluation reliability is derived may be limited. For example, evaluation reliability may be derived for pre-set combinations of imaging conditions.

[0049] [Other embodiments] The present invention can also be realized by supplying a program that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that implements one or more functions. [Explanation of Symbols]

[0050] 101 Image Processing Device 201 Evaluation Condition Setting Section 205 Display Control Unit

Claims

1. A derivation means for deriving the reliability of an evaluation based on the evaluation conditions in the evaluation of an object surface, A display control means that displays a warning regarding the evaluation conditions when the derived evaluation confidence level is below a standard value, An image processing apparatus characterized by having

2. The image processing apparatus according to claim 1, characterized in that the derivation means calculates the relative amount of movement between the object and the imaging means based on the evaluation conditions, and derives the evaluation reliability based on the calculated amount of movement.

3. The image processing apparatus according to claim 2, characterized in that the derivation means calculates the amount of movement based on the shutter speed of the imaging means and the movement speed of the imaging means and the light source.

4. The image processing apparatus according to claim 1, characterized in that the derivation means derives the evaluation reliability based on information correlated with the amount of noise in an image obtained by imaging the object irradiated with light, among the evaluation conditions.

5. The image processing apparatus according to claim 4, characterized in that the information correlated with the amount of noise in the aforementioned image is the ISO sensitivity and shutter speed of the imaging means for imaging the object, and the brightness of the light source for illuminating the object.

6. The image processing apparatus according to claim 1, further comprising evaluation means for evaluating the surface of the object based on image data obtained by imaging the object irradiated with light.

7. The image processing apparatus according to claim 6, characterized in that the evaluation means evaluates the degree of orange peel texture on the surface of the object.

8. A program for causing a computer to function as an image processing device according to any one of claims 1 to 7.

9. Based on the evaluation conditions for evaluating the object surface, the evaluation reliability is derived. If the derived evaluation confidence level is below the threshold value, a warning regarding the evaluation conditions will be displayed. An image processing method characterized by the following:

Images