• Agricultural and Biosystems Engineering
• /
• v.4 no.1
• /
• pp.16-21
• /
• 2003

In the agricultural field, a machine vision system has been widely used to automate most inspection processes especially in quality grading. Though machine vision system was very effective in quantifying geometrical quality factors, it had a deficiency in quantifying color information. This study was conducted to evaluate color of beef using machine vision system. Though measuring color of a beef using machine vision system had an advantage of covering whole lean tissue area at a time compared to a colorimeter, it revealed the problem of sensitivity depending on the system components such as types of camera, lighting conditions, and so on. The effect of color balancing control of a camera was investigated and multi-layer BP neural network based color calibration process was developed. Color calibration network model was trained using reference color patches and showed the high correlation with L*a*b* coordinates of a colorimeter. The proposed calibration process showed the successful adaptability to various measurement environments such as different types of cameras and light sources. Compared results with the proposed calibration process and MLR based calibration were also presented. Color calibration network was also successfully applied to measure the color of the beef. However, it was suggested that reflectance properties of reference materials for calibration and test materials should be considered to achieve more accurate color measurement.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.2
• /
• pp.119-129
• /
• 2006

Art psychotherapy is widely accepted as an effective tool for diagnosis and treatment of psychological disorders. Important factors for art psychotherapy diagnosis, based on the projection theory that the world of the inner mind appears in drawings, include main color and imbalance of a drawing. This paper develops a system for a machine to determine the main color and the imbalance of a drawing by color recognition and edge detection. Our proposed color recognition procedure adopts NBS(National Bureau of Standards) distance between colors in HVC(Hue, Value, Chroma) color space which is most similar to the human eye's color perception. Our edge detection procedure applies blurring, clustering and transformation to a standard color in a series. Our system considers the numbers of pixels and clusters for each color as a criterion for main color and the frequency of edge coordinates for each region for imbalance. The proposed machine procedure, verified through case studies, can help overcome the subjectivity, ambiguity and uncertainty in human decision involved in art psychotherapy.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 1986.10a
• /
• pp.83-86
• /
• 1986

In this paper, we propose the new color image segmentation algorithm using clustering method in the normalized r,g,b coordinates. The number of intrinsic clusters which are included in color image is estimated by the clustering quality measure and the initial centers of clusters are calculated by a hierarchical way. The proposed algorithm was varified by the computer simulation.

• Journal of Biosystems Engineering
• /
• v.17 no.4
• /
• pp.382-395
• /
• 1992

The surface color of several varieties of apples were expressed quantitatively in xyz chromaticity coordinates. The spectral reflectance of 'Fuji' apples were measured in 400-820 nm range by using a spectrophotometer. Based on the spectrophotometer data and the result of visual sensory test, linear regression models were developed to select wavelengths effective for sorting apples. The models utilized reflectance at single wavelength, and the difference and ratio of the reflectance at two distinct wavelengths. The model which best fitted the visual sensory test data was one utilizing the ratio of the reflectance at 618 nm and 514nm. The correlation coefficient for this model was 0.967. Several other models were also described.

• Journal of the Korea Convergence Society
• /
• v.10 no.5
• /
• pp.1-8
• /
• 2019

In this paper, we propose an improved facial skin color extraction method to solve the problem that facial surface is lost due to shadow or illumination in skin color extraction process and skin color extraction is not possible. In the conventional HSV method, when facial surface is brightly illuminated by light, the skin color component is lost in the skin color extraction process, so that a loss area appears on the face surface. In order to solve these problems, we extract the skin color, determine the elements in the H channel value range of the skin color in the HSV color space among the lost skin elements, and combine the coordinates of the lost part with the coordinates of the original image, To minimize the number of In the face detection process, the face was detected using the LBP Cascade Classifier, which represents texture feature information in the extracted skin color image. Experimental results show that the proposed method improves the detection rate and accuracy by 5.8% and 9.6%, respectively, compared with conventional RGB and HSV skin color extraction and face detection using the LBP cascade classifier method.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.23 no.1
• /
• pp.27-36
• /
• 2005

Most of flated scanners and digital cameras in prepress process utilize CCD technology. Device calibration and characterization process is needed to transform the device dependent color to the device independent color. ICC profiles for digital input devices encapsulated information relating the device values to CIELAB or CIEXYZ coordinates. The main purposes of this article is to evaluate some of the transformation methods based on ICC proposed device profiles and to propose optimal color transformation method for accurate color imaging in printing process.

• Journal of the Korea Safety Management & Science
• /
• v.10 no.4
• /
• pp.145-152
• /
• 2008

According to the Korea Agency for Technology and Standards under the Commerce Ministry, OLED device's lifetime is defined 50% drop of luminance. OLED device is self-emitting operating device, that means it becomes different color between pixels under using environment. That's reason of the different luminance drop ratio & chromaticity coordinates shift ratio with time. The problem is there is not recovered after luminance drop and color shift. We can recognize the difference of color as image sticking. First we studied when human recognize the difference of color and second we apply the method of OLED device's lifetime test that's able to check different color between pixels.

• Journal of the Optical Society of Korea
• /
• v.11 no.2
• /
• pp.67-70
• /
• 2007

A Wide Color Gamut Backlight system was studied using a three-band white Light-Emitting Diode. A three-band white light-emitting diode (LED) was fabricated using an InGaN-based blue LED chip that emits 445-nm blue peak, and a green phosphor and red phosphor that emit 535-nm green and 621-nm red peak emissions, respectively, when excited by 450-nm blue light. Using for this three-band white LED, wide color gamut backlight unit (BLU) was attained. The luminance of BLU and CIE 1931 chromaticity coordinates was $1,700Cd/m^2$ and (0.337, 0.346). Color filter matching simulations for this configuration show that the three-band white LED backlight can be enhanced by up to 16% over conventional white LED backlight color gamut.

• Proceedings of the Safety Management and Science Conference
• /
• 2008.11a
• /
• pp.131-143
• /
• 2008

According to the Korea Agency for Technology and Standards under the Commerce Ministry, OLED device's lifetime is defined 50% drop of luminance. OLED device is self-emitting operating device, that means it becomes different color between pixels under using environment. That's reason of the different luminance drop ratio & chromaticity coordinates shift ratio with time. The problem is there is not recovered after luminace drop and color shift. We can recognize the difference of color as image sticking. First we studied when human recognize the difference of color and second we apply the method of OLED device's lifetime test that's able to check different color between pixels

• Journal of Biosystems Engineering
• /
• v.32 no.3
• /
• pp.160-165
• /
• 2007

This study was conducted to evaluate beef using a color machine vision system. The machine vision system has an advantage to measure larger area than a colorimeter and also could measure other quality factors like distribution of fats. However, the machine vision measurement is affected by system components. To measure the beef color with the machine vision system, the effect of color balancing control was tested and calibration model was developed. Neural network for color calibration which learned reference color patches showed a high correlation with colorimeter in L*a*b* coordinates and had an adaptability at various measurement environments. The trained network showed a very high correlation with the colorimeter when measuring beef color.