• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.189-196
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• 2008

In this paper, a CMOS digital image sensor, which consists of A/D conversion, motion estimation circuits, and an attention module for ROI (Region of Interest) detection is presented. The functions of A/D conversion and motion estimation are implemented by $0.6{\mu}m$ CMOS processing circuit as hardware, and the attention module is implemented outside the circuit as software currently. Attention modules are taken to improve limited applications of the smart image sensor. The current smart image sensor responses to the changes of intensity, and uses the integration time to estimate motion. Therefore it is limited in its applications. To make up for inherent property of the sensor from circuit design and extend its applications we decide to introduce perception solutions to the image sensor. Attention modules for still and moving images are employed to achieve such purposes. The suggested approach makes the smart image sensor available with additional functions for such cases that motion estimation or intensity changes are not observed. Experimental result shows the usefulness and extension of the image sensor.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.47-55
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• 2003

In this paper, we propose a new approach to detect peculiar features of license plates using intensity vector and composite color component in order to extract license plates from parking regulation images, which is captured in various locations around the front or the rear of cars at various times and places, and in which complex background is included. We fundamentally use both features that intensity value repeats frequently increasing and decreasing because intensity is obviously different at numerics and background, and that color is uniform in the area of license plates. First, we search each row at regular intervals starting from the bottom of a license-plate image, and we set up a rough region for a certain zone in which tile sign of intensity vector changes frequently enough and color of license plate is detected enough, assuming it as a candidate location of a license plate. And then, we extract an elaborate area of a license plate by projecting vertical edges horizontally and vertically. Here, type of cars, such as the urinate and the public, is easily classified according to the color of extracted plates. We used 200 actual regulation images, which are captured at various times and places, to evaluate the performance of the proposed method. As a result, the proposed method showed extraction rate of 96%, which is 9% higher than the previous method using only intensity vector.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.483-488
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• 2015

This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.435-437
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• 2001

본 논문은 BMI (Background Marking 1)을 개선하여 차량의 번호판정 보를 보다 신속히 추출하는 방법에 대한 연구이다. BMI은 입력된 영상에서 각각의 화소를 비교하여 특정색상을 최고치인 255로 지정하고, 그 이외의 화소는 최저치인 0으로 표시하는 방법이다. 하지만 이 방법은 모든 화소를 처리함으로써 검색시간이 많이 소요된다는 단점을 가지고 있다. BM2는 이러한 단점을 개선하여 빠른 차량 번호판 검색 및 추출을 가능하도록 하였다. 또한 기존에 제시된 히스토그램에 기초한 검색방법은 명암의 변화에 따른 추론방법으로 조명과 잡음에 약하다는 단점을 가진다. BM2는 기존 방법과 달리 특정색상을 추출함으로써 명암의 변화에 강한 특징을 가지도록 하였다. 제안된 방법을 여러 가지지 차량 종류에 따른 영상에 적용하여 BMI보다 우수한 성능을 검증하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.375-382
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• 2016

In this paper, we presents a signatures verification by using the nonlinear quantization histogram of polar coordinate based on multi-dimensional adjacent pixel intensity difference. The multi-dimensional adjacent pixel intensity difference is calculated from an intensity difference between a pair of pixels in a horizontal, vertical, diagonal, and opposite diagonal directions centering around the reference pixel. The polar coordinate is converted from the rectangular coordinate by making a pair of horizontal and vertical difference, and diagonal and opposite diagonal difference, respectively. The nonlinear quantization histogram is also calculated from nonuniformly quantizing the polar coordinate value by using the Lloyd algorithm, which is the recursive method. The polar coordinate histogram of 4-directional intensity difference is applied not only for more considering the corelation between pixels but also for reducing the calculation load by decreasing the number of histogram. The nonlinear quantization is also applied not only to still more reflect an attribute of intensity variations between pixels but also to obtain the low level histogram. The proposed method has been applied to verified 90(3 persons * 30 signatures/person) images of 256*256 pixels based on a matching measures of city-block, Euclidean, ordinal value, and normalized cross-correlation coefficient. The experimental results show that the proposed method has a superior to the linear quantization histogram, and Euclidean distance is also the optimal matching measure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.820-823
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• 2013

Recently, the need for improving image quality of the image is increasing in various fields smartphones, cameras, and portable devices. How a significant impact on improving image quality of the image is a contrast enhancement, as a representative method to improve the contrast, the process of histogram equalization, various studies have been made. However, the method of histogram equalization general, by readjusting the only brightness, when the image histogram is biased to one side, due to changes in the excess brightness, distortions such as blocking phenomenon occurs. In this paper, we provide a contrast enhancement techniques through the compression and re-distribution of a well-balanced average brightness of the histogram distribution. By be differential compression histogram based on the histogram frequency in order to suppress the supersaturation phenomenon due to the increase in contrast ratio excessive repositioning well-balanced histogram lopsided, the proposed method, the balance of the brightness of the image I want to to take. The experimental results, the image brightness is balanced manner compared to conventional methods, the proposed method showed a good effect to improve the contrast without supersaturation phenomenon as compared with the conventional methods.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.119-130
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• 2013

In this paper, we propose a new color image enhancement method to improve the color saturation as well as luminance contrast in the YCbCr color space. The proposed method uses the maximum color difference table to compensate the perceived saturation changes due to luminance contrast changes. To improve the color saturation, the method first calculates the weighting factor by using the maximum color difference table and then multiplies the weighting factor to the input color difference signals. In this step, it maps color difference signals to proper color region to prevent the color distortion by considering the correlation of color saturations depending on the luminance and hue. The experimental results show that our method effectively improves color saturation compared to the conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1661-1666
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• 2010

Due to light condition or shadow around camera, acquired image sequence is often degraded by intensity fluctuation. This artifact is called luminance flicker. As the luminance flicker corrupts the performance of motion estimation or object detection, it should be corrected before further processing. In this paper, we analyze the flicker generation model and propose the new algorithm for flicker reduction. The proposed algorithm considers gain and offset parameter separately, and stabilizes the luminance fluctuation based on these parameters. We show the performance of the proposed method by testing on the sequence with artificially added luminance flicker and real sequence with object motion.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.76-88
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• 2010

Recently, LED background image devices are used for the production of broadcasting programs. But the effective advantages of LED background image devices are not realized for good HD video quality because the correlations between lighting sources and LED background image devices are not analyzed yet. In this paper, we analyze the color change and light intensity that lighting sources and the light intensity ratio of LED background images influence on a subject, making use of equipments used in real broadcasting, and examine the correlations between HD video quality and the light intensity ratio of LED background images. As a result in this experiment, the video is most expressed having an 20[IRE] effect on a subject when the light intensity of LED background image is 6%. When the LED background image is light, the light and darkness of video is distorted and when the LED background image is dark, the colors of image are distorted.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.137-146
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• 2015

In this paper, we propose a pothole detection method using various features of intensity and motion. Segmentation, decision steps of pothole detection are processed according to the values which are derived from feature characteristics. For segmentation using intensity, we use a binarization method using histogram to separate pothole region from background. For segmentation using motion, we filter using high pass filter and get standard deviation value. This value is divided by regression value according to camera environment such as photographing angle, height, velocity, etc. We get binary image by histogram based binarization. For decision, candidate regions are decided whether pothole or not using comparison of candidate and background's features. Experimental results show that our proposed pothole detection method has better results than existing methods and good performance in discrimination between pothole and similar patterns.