• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.266-270
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• 2016

In this paper, we propose a technique of drowsiness detection using machine vision. The drowsiness of vehicle driver is often the primary cause of motor vehicle accidents. Therefore, the checking of eye images for detecting drowsiness status of driver is critical for preventing these accidents. In our suggested method, we analyze the changes of histogram and edge of eye region images which are acquired using CCD camera. We developed a drowsiness detection system using the histogram and edge change information. The experimental results show that our proposed method enhances the accuracy of detecting drowsiness nearly to 98%, and can be used for preventing vehicle accidents due to the drowsiness of drivers.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.124-133
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• 1994

Many of non-contact measuring systems are used to estimate surface characteristics owing to their advantages of high speed and undanaged test. In this paper, a new measuring system is proposed to acquire image from CCD camera through back light illumination. Lowpass filter is very useful in view of noise removal and optimum binary image can be made through histogram equalization which is one of the histogram technique to maximize brightness intensity between workpiece and background. Laplacian operator is used to detect workpiece edge from binary image. In case of image treatment applying Laplacian operator, surface roughness is calculated by introducing conversion coefficient for coordinate of pixel which edge is composed of. In summary, the work is concerned with the development of a new technique for roughness measurement by the image processing in turning.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.332-345
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• 2010

A unified image enhancement method is proposed for high-resolution image which based on color constancy and histogram equalization using edge region. To speed up the method, smaller image is used when parameters of color constancy and histogram equalization are determined. In the color constancy process, nth-derivative of gaussian is applied to x and y axis separately in order to estimate the color of the illumination rapidly. In the histogram equalization process, the histogram obtained from near-edge region is used for the histogram equalization. In the experiments, high-resolution images taken by digital camcorder are used for verifying the performance of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1603-1613
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• 1995

The goal of enhancement is to improve the perceptual aspect and visual appearance of images for human viewers. The objectives of image enhancement vary according to its specific application and an image enhancement algorithms used for a specific objective may not be accepted in some other applications. In this paper we review some of conventional enhancement techniques, such as global histogram equalization(GHE), local histogram equalization(LHE), clipped histogram equalization(CHE). We also describe some modified version of these algorithms. The proposed method is to detect detail information. We distinquish edge from nonedge and apply histigram equalization respectively. Simulation results demonstrate the performance of the proposed method for medical image.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.126-131
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• 1998

In computer vision system of modern industry precise measuring has lots of dfficulties because of measurement error due to distortion phenomenon. Among the difficulties, the distortion of edge is regraded as a dominent problem. which is caused by the vlurred image. The blurred image apperar when camera can not discriminate its precise focus. So. it is very important to decide focus of lens and to develop algorithm in order to correct distortion phenomenon. Thus. discrimination criteria obtained by image information of precise focus must be fixed in advance. The gray level histogram of image acquired from blurred edge tends to show a uniform distribution. Bimodal intensity histogram is related with condition of focus, and it is possible to find good condition of focus by using bimodal histogram of entropy.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.23-30
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• 2016

In this paper, we propose an adaptive histogram projection technique for dynamic range compression and an efficient detail enhancement method which is enhancing strong edge while reducing noise. First, The high dynamic range image is divided into low-pass component and high-pass component by applying 'guided image filtering'. After applying 'guided filter' to high dynamic range image, second, the low-pass component of the image is compressed into 8-bit with the adaptive histogram projection technique which is using global standard deviation value of whole image. Third, the high-pass component of the image adaptively reduces noise and intensifies the strong edges using standard deviation value in local path of the guided filter. Lastly, the monitor display image is summed up with the compressed low-pass component and the edge-intensified high-pass component. At the end of this paper, the experimental result show that the suggested technique can be applied properly to the IR images of various scenes.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.983-991
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• 2019

Histogram equalization method is a popular contrast enhancement technique. However, there are some drawbacks, namely, over-enhancement, under-enhancement, structure information loss, and noise amplification. In this paper, we propose an edge-enhancing histogram equalization algorithm while suppressing over-enhancement simultaneously. Firstly, over-enhancement is suppressed by clipping a transfer function, then, edge enhancement is achieved by using guided image filter. Experiments are carried out to evaluate the performance of the various HE algorithms. As a result, both qualitative and quantitative assessment showed that the proposed algorithm successfully suppressed over-enhancement while enhancing edges.

• Proceedings of the KAIS Fall Conference
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• 2006.11a
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• pp.220-224
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• 2006

The text to be included in the natural images has many important information in the natural image. Therefore, if we can extract the text in natural images, It can be applied to many important applications. In this paper, we propose a text region extraction method using pattern histogram of character-edge map. We extract the edges with the Canny edge detector and creates 16 kind of edge map from an extracted edges. And then we make a character-edge map of 8 kinds that have a character feature with a combination of an edge map. We extract text region using 8 kinds of character-edge map and 16 kind of edge map. Verification of text candidate region uses analysis of a character-edge map pattern histogram and structural feature of text region. The method to propose experimented with various kind of the natural images. The proposed approach extracted text region from a natural images to have been composed of a complex background, various letters, various text colors effectively.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.12-14
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• 2006

This paper presents a novel scene change detection method using intra prediction mode and edge direction in H.264/AVC. When scene change occurs, there are less temporal correlation between frames, most of macro-blocks encoded in intra mode. Using this property, the method calculates the percentage of intra mode blocks in each predictive frame in order to get candidates of scene change frame. To further find scene change, we obtain edge histogram of each candidates by using eight prediction direction of intra prediction mode in H.264/AVC. We detect scene change frames with $\iota^1$-norm of edge histograms. The experimental results show that the method is efficient and robust.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1146-1151
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• 2019

Histogram H is an x-monotone rectilinear polygon with a horizontal edge, called by a base, connecting the leftmost vertical edge and the rightmost vertical edge. Here the rectilinear polygon is a polygon with only horizontal and vertical edges and the x- monotone polygon P is a polygon in which every line orthogonal to the x-axis intersects P at most twice. Walking counterclockwise on the boundary of a histogram H yields a sequence of left turns and right turns at its vertices. Conversely, a given sequence of the turns at the vertices can be realized by a histogram. In this paper, we consider the problem of finding a histogram to realize a given turn sequence. Particularly, we will find the histograms to minimize its area and its bounding box. It will be shown that both of the problems can be solved by linear time algorithms.