Abstract:
An object is to ensure clear and easy quantification of the textures such as metallic texture and shiny texture of pearl pigment and to rationalize comparison inspection between an inspection object and a reference object. A coloring inspection apparatus 1 includes a camera 2 that is configured to have three spectral sensitivities (S1(λ), S2(λ), S3(λ)) linearly and equivalently converted to a CIE XYZ color matching function, an arithmetic processing unit 3 that is configured to obtain and compute coloring data by conversion of an image which has three spectral sensitivities and is obtained by the camera 2 into tristimulus values X, Y and Z in a CIE XYZ color system, and lighting units 6 that are configured to illuminate an automobile 5 as an example of measuring object. The coloring inspection apparatus 1 computes a color distribution consistency index that represents a ratio of overlap of two xyz chromaticity histogram distributions of an inspection object Q and a reference object R, so as to inspect color.
Abstract:
An object is to ensure clear and easy quantification of the textures such as metallic texture and shiny texture of pearl pigment and to rationalize comparison inspection between an inspection object and a reference object. A coloring inspection apparatus 1 includes a camera 2 that is configured to have three spectral sensitivities (S1(λ), S2(λ), S3(λ)) linearly and equivalently converted to a CIE XYZ color matching function, an arithmetic processing unit 3 that is configured to obtain and compute coloring data by conversion of an image which has three spectral sensitivities and is obtained by the camera 2 into tristimulus values X, Y and Z in a CIE XYZ color system, and lighting units 6 that are configured to illuminate an automobile 5 as an example of measuring object. The coloring inspection apparatus 1 computes a color distribution consistency index that represents a ratio of overlap of two xyz chromaticity histogram distributions of an inspection object Q and a reference object R, so as to inspect color.
Abstract:
An object is to accurately provide the user with color fidelity information irrespective of difference in the time of day when or in the location where a commercial product is photographed and prevent mismatching of the user's selection of the commercial product. A color fidelity environment correction system 1 includes a camera 2 and a computer 5 that is connectable with the camera 2, a tablet terminal 3 and a display device 4 and is configured to include a CPU, a ROM, a RAM, a hard disk drive and a bus line. A red vehicle 6 is photographed with the camera 2 (RC-500) in a plant or the like, and XYZ color fidelity images are recorded in a storage unit 51 of the computer 5. Another blue vehicle 7 is photographed with the tablet terminal 3 in the open air, and an RGB color image is stored in a storage unit 52. An RGB color image of the red color vehicle is created with replacement of the blue color of the RGB color image of the vehicle 7 with red color of the 3-band visual sensitivity images S1i, S2i and S3i of the vehicle 6 and is displayed on the display device 4 or is displayed with the RGB color image of the blue vehicle 7 in a comparative manner.
Abstract:
An object is to quantify the texture such as irregularity and gloss of a metal surface. Centers of Lab chromaticity distributions are identified (S145), and one of the Lab chromaticity distribution is entirely shifted (mapped) by deviations ΔA, ΔB and ΔL of a central coordinate, such that one of central coordinates of two distributions U1(L,a,b) and U2(L,a,b) matches with the other central coordinate (S146). A texture spread index that indicates a difference in spatial spread is then computed (S147). This configuration computes the spatial spread of the Lab chromaticity distribution in a three-dimensional space, and quantifies the irregularity of an inspection plane by diffraction phenomenon of illumination light. The difference in spread other than the color is applicable to evaluation of the irregularity of the metal surface or the like.
Abstract:
An object is to quantify the texture such as irregularity and gloss of a metal surface. Centers of Lab chromaticity distributions are identified (S145), and one of the Lab chromaticity distribution is entirely shifted (mapped) by deviations ΔA, ΔB and ΔL of a central coordinate, such that one of central coordinates of two distributions U1(L,a,b) and U2(L,a,b) matches with the other central coordinate (S146). A texture spread index that indicates a difference in spatial spread is then computed (S147). This configuration computes the spatial spread of the Lab chromaticity distribution in a three-dimensional space, and quantifies the irregularity of an inspection plane by diffraction phenomenon of illumination light. The difference in spread other than the color is applicable to evaluation of the irregularity of the metal surface or the like.
Abstract:
Object:An object is to quantify the roughness of a test surface by scattering and diffraction of illumination light and to evaluate the matching degree of surface roughness separately from color based on a difference in roughness.Solution to ProblemA surface roughness determination apparatus 1 using a white light source includes an arithmetic processing unit 3 configured to convert 3-band visual sensitivity images S1i, S2i and S3i, which respectively have three spectral sensitivities (S1(λ), S2(λ) and S3(λ)) subjected to linear transformation so as to be equivalent to a CIE XYZ color matching function and are obtained from a surface 5 by a two-dimensional colorimeter 2 using the three spectral sensitivities (S1(λ), S2(λ) and S3(λ)), into tristimulus values X, Y and Z in a CIE XYZ color system and perform arithmetic operations. This arithmetic processing unit 3 includes a color difference calculator configured to calculate a color difference ΔE; a color space histogram distribution creator configured to divide an examination area of coordinates corresponding to a color space in the XYZ color system by grids G and respectively integrate the numbers of pixels on a test surface and on a reference surface included in each of the grids G, so as to create color space histogram distributions in the XYZ color system; a surface roughness index calculator configured to calculate a surface roughness index M indicating a difference between the two color space histogram distributions of the test surface and the reference surface with or without an offset correction; a surface roughness measurement data storage unit configured to store a measured surface roughness value Ra actually measured by a roughness meter; and a function setter configured to set at least one of a first calibration curve function L1 indicating a correlation of the measured surface roughness value Ra to a surface roughness evaluation index Est, a second calibration curve function L2 indicating a correlation of the measured surface roughness value Ra to the color difference ΔE, a third calibration curve function L3 indicating a correlation of the measured surface roughness value Ra to the surface roughness index M calculated without the offset correction and a fourth calibration curve function indicating a correlation of the measured surface roughness value Ra to the surface roughness index M calculated with the offset correction.
Abstract:
An object is to accurately provide the user with color fidelity information irrespective of difference in the time of day when or in the location where a commercial product is photographed and prevent mismatching of the user's selection of the commercial product. A color fidelity environment correction system 1 includes a camera 2 and a computer 5 that is connectable with the camera 2, a tablet terminal 3 and a display device 4 and is configured to include a CPU, a ROM, a RAM, a hard disk drive and a bus line. A red vehicle 6 is photographed with the camera 2 (RC-500) in a plant or the like, and XYZ color fidelity images are recorded in a storage unit 51 of the computer 5. Another blue vehicle 7 is photographed with the tablet terminal 3 in the open air, and an RGB color image is stored in a storage unit 52. An RGB color image of the red color vehicle is created with replacement of the blue color of the RGB color image of the vehicle 7 with red color of the 3-band visual sensitivity images S1i, S2i and S3i of the vehicle 6 and is displayed on the display device 4 or is displayed with the RGB color image of the blue vehicle 7 in a comparative manner.