• The KIPS Transactions:PartB
• /
• v.17B no.3
• /
• pp.207-214
• /
• 2010

A method of the region extraction and recognition of a traffic light and speed sign board in the real road environment is proposed. Traffic light was recognized by using brightness and color information based on HSI color model. Speed sign board was extracted by measuring red intensity from the HSI color information We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. The proposed algorithm shows a robust recognition rate in the image sequence which includes traffic light and speed sign board.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.12
• /
• pp.174-182
• /
• 2015

In this paper, we developed the small size RGB sensor that recognizes a long distance using a low-cost color sensor. Light receiving portion of the sensor was used as a camera lens for far distance recognition, and illuminating unit was increased the strength of the light by using a high-power white LED and a lens mounted on the reflector. RGB color recognition algorithm consists of the learning process and the realtime recognition process. We obtain a normalized RGB color reference data in the learning process using the specimens painted with target colors, and classifies the three colors using the Mahalanobis distance in recognition process. We apply the developed the RGB color recognition sensor to a prototype of the part classification system and evaluate the performance of its.

• Journal of Multimedia Information System
• /
• v.6 no.4
• /
• pp.185-190
• /
• 2019

For future autonomous cars, it is necessary to recognize various surrounding environments such as lanes, traffic lights, and vehicles. This paper presents a method of speed sign recognition from a single image in automatic driving assistance systems. The detection step with the proposed method emphasizes the color attributes in modified YUV color space because speed sign area is affected by color. The proposed method is further improved by extracting the digits from the highlighted circle region. A sequential cascade AdaBoost classifier is then used in the recognition step for real-time processing. Experimental results show the performance of the proposed algorithm is superior to that of conventional algorithms for various speed signs and real-world conditions.

• Journal of the Optical Society of Korea
• /
• v.15 no.4
• /
• pp.335-339
• /
• 2011

Recently, we reported a single input channel joint transform correlator for the color pattern recognition which decomposes the input color image into three R, G, and B gray components and adds those components into a single gray image in the input plane. This technique has the merit of a single input channel instead of three input channels. However, we found this technique has some problems with discrimination impossibility in the case of a simple primary color pattern which results in the same gray level through the addition process. Thus, we propose a modified coding technique which selectively recombines the decomposed three R, G, and B gray components instead of the simple adding process. Simulated results show that the modified coding technique can accurately discriminate a variety of kinds of color images.

• Journal of Broadcast Engineering
• /
• v.23 no.1
• /
• pp.93-103
• /
• 2018

This paper presents a method for speed limit sign recognition in images. Conventional sign recognition methods decreases recognition accuracy because they are very sensitive and include repeated features. The proposed method emphasizes color attributes based on the weighted YUV color space. Moreover, the recognition accuracy can be improved by extracting the local region of interest (ROI) in the candidates. The proposed method uses the Haar features and the Adaboost classifier for recognition. Experimental results confirm that the proposed algorithm is superior to conventional algorithms under various speed signs and conditions.

• 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.

• The KIPS Transactions:PartB
• /
• v.15B no.4
• /
• pp.285-292
• /
• 2008

Color histograms have been used as feature vectors to characterize the color features of given images, but they have a limitation in efficiency by generating high-dimensional feature vectors. In this paper, we present a method to reduce the dimension of the feature vectors by applying PCA (principal components analysis) to the color histogram of a given vehicle image. With SVM (support vector machine) method, the dimension-reduced feature vectors are used to recognize the colors of vehicles. After reducing the dimension of the feature vector by a factor of 32, the successful recognition rate is reduced only 1.42% compared to the case when we use original feature vectors. Moreover, the computation time for the color recognition is reduced by a factor of 31, so we could recognize the colors efficiently.

• Journal of Fashion Business
• /
• v.20 no.4
• /
• pp.50-71
• /
• 2016

This study analyzed the recognition rate of QR codes printed by digital transfer textile printing for mobile application. The purpose was to identify conditions that increase recognition rates of QR codes printed on textile, in order to increase utility of QR codes in the textile and fashion industries. The study focused on differences in the color of the QR codes and denier, which is a unit of textile fineness measurement, of the textile on which the QR codes were printed. And the recognition rates of QR codes according to the color and denier were analyzed. According to the result of this study, the colors of QR codes had an effect on the recognition of the codes by mobile applications. Specifically, strong contrast, i.e., bright background and relatively dark module, increased the recognition rate of the QR codes. Digital transfer textile printing tend to change the hue of red and yellow and increase brightness, and change in the printed colors also had an effect on the recognition rate of QR codes. There was a clear difference in the color and recognition rate of the printed QR code according to the denier of the textile, and this suggests denier has an effect on the recognition rate. The findings in this study can provide basic data for future research on QR codes digital printed on textile.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.3D
• /
• pp.519-525
• /
• 2006

The traditional area-based matching or efficient matching methods using epipolar geometry and height restriction of stereo images, which have a confined search space for image matching, have still some disadvantages such as mismatching and timeconsuming, especially in the dense metropolitan city that very high and similar buildings exist. To solve these problems, a new image matching method through building recognition has been presented. This paper described building recognition in color stereo images using edge and color information as a elementary study of new matching scheme. We introduce the modified Hausdorff distance for using edge information, and the modified color indexing with 3-D RGB histogram for using color information. Color information or edge information alone is not enough to find conjugate building pairs. For edge information only, building recognition rate shows 46.5%, for color information only, 7.1%. However, building recognition rate distinctly increase 78.5% when both information are combined.

• The KIPS Transactions:PartB
• /
• v.9B no.4
• /
• pp.491-500
• /
• 2002

In this paper, we propose a real-time face detection and recognition system by using skin color informations, geometrical feature vectors of face, and facial angle informations from color face image. The proposed algorithm improved face region extraction efficiency by using skin color informations on the HSI color coordinate and face edge information. And also, it improved face recognition efficiency by using geometrical feature vectors of face and facial angles from the extracted face region image. In the experiment, the proposed algorithm shows more improved recognition efficiency as well as face region extraction efficiency than conventional methods.