• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.92-98
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• 2022

This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.2
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• pp.139-146
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• 2020

The camouflage pattern was difficult to distinguish from the surrounding background, so it was difficult to classify the object and the background image when the color image is used as the training data of deep-learning. In this paper, we proposed a red-green color blindness image transformation method using the principle that people of red-green blindness distinguish green color better than ordinary people. Experimental results show that the camouflage soldier's recognition performance improved by proposed a deep learning model of the ensemble technique using the imitated red-green-blind image data and the original color image data.

• Journal of Korean Ophthalmic Optics Society
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• v.12 no.3
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• pp.89-91
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• 2007

Color vision test was conducted to elementary school students at age of 9 to 13, with total subject number of 598 which live in Gwang Ju area. 325 (54.3%) boys and 273 (45.7%) girls were subjected using Hahn Color Vision test to find out color recognition problems. 1. Ratios of color vision abnomality were 6.25% in 9 year old students, 9.2% in 10 year old students, 8.4% in 12 year old students, 7.8% in 13 year old students, which means 7.9% of the total 598 subjects had color recognition matters. 2. Red-Green dyschromatopsia was 7.8% of the total 598 subjects which includes most of subjects. None of them had green-yellow recognition problem. Full dyschromatopsia had frequency of 0.2%. 3. 10.7% of boys had color vision abnormality, while 10.7% of girls had color vision abnormality, which means that boys have color recognition problems with higher rate than girls.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.33-39
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• 2014

Automatic driving needs many functions such as the obstacle recognition, the lane recognition, and the lane change, etc. In this paper, we realized a system which automatically drove the three-kinds of vehicle driving course, to introduce and apply the concept of 'color recognition' that expands the scope of 'lane recognition' for vehicle driving. We made the reduced each course compared with RC(Radio Control) car size, and controlled the steering considering the position and the slope of the detection line and the speed. Because the RC car does not have the brake function, we consider the speed and the position of the detection line to stop the RC car.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.65-72
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• 2006

The traffic lights detection and recognition system is an essential module of the driver warning and assistance system. A method which is a color vision-based real time detection and recognition of traffic lights is presented in this paper This method has four main modules : traffic signals lights detection module, traffic lights boundary candidate determination module, boundary detection module and recognition module. In traffic signals lights detection module and boundary detection module, the color thresholding and the subtraction value of saturation and intensity in HSI color space and detection probability mask for lights detection are used to segment the image. In traffic lights boundary candidate determination module, the detection mask of traffic lights boundary is proposed. For the recognition module, the AND operator is applied to the results of two detection modules. The input data for this method is the color image sequence taken from a moving vehicle by a color video camera. The recorded image data was transformed by zooming function of the camera. And traffic lights detection and recognition experimental results was presented in this zoomed image sequence.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.3
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• pp.40-46
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• 2006

Automatic recognition of container identifier is one of key factor to implement port automation and increase distribution throughput. In this paper, I propose a method of container identifier recognition on various input images using color based edge detection and character verification algorithm, I tested the proposed method on 350 container images and it showed good results.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.87-101
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• 2002

In this paper, we proposes the car plate recognition and describe the parking control system using the proposed car plate recognition algorithm. The car plate recognition system using color information and fuzzy c-means algorithm consists of the extraction part of a car plate from a car image and the recognition part of characters in the extracted car plate. This paper eliminates green noise from car image using the mode smoothing and extract plate region using green and white information of RGB color. The codes of extracted plate region is extracted by histogram based approach method and is recognized by fuzzy c-means algorithm. For experimental, we tested 80 car images. We shows that the proposed extraction method is better than that from the color information of RGB and HSI, respectively. So, we can know that the proposed car plate recognition method using fuzzy c-means algorithm was very efficient. We develop the parking control system using the proposed car plate recognition method, which showed performance improvement by the experimental results.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.809-818
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• 2007

In this thesis, the color information is used to extract the traffic sign territory, and for recognizing the extracted image, it proposes the traffic sign recognition system that applies the error back propagation algorithm. The proposed method analyzes the color of traffic sign to extract and recognize the possible territory of traffic sign. The method of extracting the possible territory is to use the characteristics of YUV, YIQ, and CMYK color space from the RGB color space. Morphology uses the geometric characteristics of traffic sign to make the image segmentation. The recognition of traffic signs can be recognized by using the error back propagation algorithm. As a result of the experiment, the proposed system has proven its outstanding capability in extraction and recognition of candidate territory without the influence of differences in lighting and input image in various sizes.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.336-344
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• 2012

As an important part of the Computer Vision, the object recognition and tracking function has infinite possibilities range from motion recognition to aerospace applications. One of methods to improve accuracy of the object recognition, are uses colors which have robustness of orientation, scale and occlusion. Computational cost for extracting features can be reduced by using color. Also, for fast object recognition, predicting the location of the object recognition in a smaller area is more effective than lowering accuracy of the algorithm. In this paper, we propose a method that uses SURF descriptors which applied with color model for improving recognition accuracy and combines with Kalman filter which is Motion estimation algorithm for fast object tracking. As a result, the proposed method classified objects which have same patterns with different colors and showed fast tracking results by performing recognition in ROI which estimates future motion of an object.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.173-174
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• 2009

Color harmony will look good formative elements of the basic lines, shapes and colors. In this paper, we present the implementation of Johannes Itten's color balance. Yellow, red, blue, on the basis of the first color mixing between the index and second color is placed. 12 color balance made by placing a third color between the first color and second color. we recognize this 12 color balance. Edge is detected using the Canny edge operator and labeling and clustering was expressed through the colors.