• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.170-179
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• 1993

In this study, self-organized neural network is used to solve the vorrespondence problem of the axial stereo image. Edge points are extracted from a pair of stereo images and then the edge points of rear image are assined to the output nodes of neural network. In the matching process, the two input nodes of neural networks are supplied with the coordi- nates of the edge point selected randomly from the front image. This input data activate optimal output node and its neighbor nodes whose coordinates are thought to be correspondence point for the present input data, and then their weights are allowed to updated. After several iterations of updating, the weights whose coordinates represent rear edge point are converged to the coordinates of the correspondence points in the front image. Because of the feature map properties of self-organized neural network, noise-free and smoothed depth data can be achieved.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1007-1010
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• 2002

In this paper, we present a new blocking artifact reduction algorithm using interpolation and signal adaptive filter (SAF) based on the edge map. Generally, block-based coding, such as JPEG and MPEG, is the most popular image compression method. However, for high compression it produces noticeable blocking and ringing artifacts in the decoded image. In proposed method, all the block is classified into low and high frequency blocks in block classification procedure. And edge map is obtained by using Sobel operator on decoded image. And according to the block property we applied blocking artifacts reduction algorithm. Namely, four neighbor low frequency block is participated in interpolation based on edge map. And ringing artifacts is removed by applying a signal adaptive filter around the edge using edge map in high frequency block. The computer simulation results confirmed a better performance by the proposed method in both the subjective and objective image qualities.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.46-54
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• 2008

Most commercial CCD/CMOS image sensors have CFA(Color Filter Array) where each pixel gathers light of a selective color to reduce the sensor size and cost. There are many algorithms proposed to reconstruct the original clolr image by adopting pettern recognition of regularization methods to name a few. However the resulting image still suffer from errors such as flase color, zipper effect. In this paper we propose an adaptive edge weight demosaicking algorithm that is based on POCS(Projection Onto Convex Sets) not only to improve the entire image's PSNR but also to reduce the edge region's errors that affect subjective image quality. As a result, the proposed algorithm reconstruct better quality images especially at the edge region.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.288-294
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• 2008

In this paper, we proposed an algorithm of edge enhancement to improve image visibility of mobile phone camera. For naturally edge enhancement, we grasps edge characteristic in image and applied to the most appropriate enhancement value adaptively about each characteristics. Namely, It applies 2D high pass filter where in the edge characteristics which judge in the first In compliance with the edge condition which is subdivided more with secondary it will be able to apply the process which able to adaptive edge enhancement to improve image visibility. It joins in and it is an existing algorithm that simply a lies 2D high pass filter where and it is identical in the image whole it will be able to improve the side effects of ringing actual condition etc. It considers the effectiveness of the hardware resource with the hardware of the algorithm which is developed and algorithm the maximum simply, it developed and simulation of the algorithm which is proposed it led and algorithm of existing and it compared and is improved the result which it confirmed.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1865-1872
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• 1997

This paper proposes not only the thresholding problem which has been one of the major problems in the pre-existing edge detection method but also the removal of blurring effect occurred at the edge regions due to the smoothing process. The structure of a given image is assigned as one of the three predefined image structure classes by evaluating its toll membership value to each reference structure class:The structure of an image belongs to the structure class which has the least cost value with the image. Upon the structure class assigned, noise removal and edge extraction precesses are performed, e.g., the smoothing algorithm is applied to the image if its structure belongs to the pure noise region class; edge extraction while removing the noise is performed simultaneously if the edge structure class. The proposed method shows that preventing the blurring effect can be usually seen in the edge images and extracting the edges with no using thresholding value by the experiments.

• The Journal of Information Technology
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• v.6 no.1
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• pp.71-84
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• 2003

In this paper, it is presented the efficient system for data recognition using the proposed binary code images. The proposed algorithm finds the position of binary image. Through the process of the block region classification, it is classified each block with the edge region using the value of gray level only. Each block region is divided horizontal and vertical edge region. If horizontal edge region blocks are classified over six blocks in any region, the proposed algorithm should search the vertical edge region in the start point of the horizontal edge region. If vertical edge region blocks were found over ten blocks in vertical region, the code image would found. Practical code region is acquired from the rate of the total edge region that is computed from the binary image that is processed with the average value. In case of the wrong rate, it is restarted the code search in the point after start point and the total process is followed. It has a short time than the before process time because it had classified block information. The block processing is faster thant the total process. The proposed system acquires the image from the digital camera and makes binary image from the acquired image. Finally, the proposed system extracts various characters from the binary image.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1368-1370
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• 1996

The Information of Edges which takes small area comparing with the total image is very important in DNA images as well as general images. DNA image is the object should be managed by computing and it's demanding information is less than general images, but the accuracy is more important In a huge DNA image processing system such as DNA Information Bank, the performance depends on the size of image. In this paper, we extract the edge information and make it as a binary image. To reduce the size of the original image, it was applied by JPEG image compression method. The compressed image is combined with edge information when they are restored. As a result, Both the image compression ratio and restoration quality are optimized without the loss of critical information.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.171-181
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• 2005

The purpose of this paper is two-fold: 1) A novel algorithm in order to extract lane-related information from road images is presented; 2) Design specifications of an image processing onboard unit capable of extracting lane­related information in real-time is also presented. Obtaining precise information from road images requires many features due to the effects of noise that eventually leads to long processing time. By exploiting a FPGA and DSP, we solve the problem of real-time processing. Due to the fact that image processing of road images relies largely on edge features, the FPGA is adopted in the hardware design. The schematic configuration of the FPGA is optimized in order to perform 3 $\times$ 3 Sobel edge extraction. The DSP carries out high-level image processing of recognition, decision, estimation, etc. The proposed algorithm uses edge features to define an Edge Distribution Function (EDF), which is a histogram of edge magnitude with respect to the edge orientation angle. The EDF enables the edge-related information and lane-related to be connected. The performance of the proposed system is verified through the extraction of lane-related information. The experimental results show the robustness of the proposed algorithm and a processing speed of more than 25 frames per second, which is considered quite successful.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.81-91
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• 2005

In this paper we present a novel approach for image retrieval using color and edge information. We take into account the HSI(Hue, Saturation and Intensity) color space instead of RGB space, which emphasizes more on visual perception. In our system colors in an image are clustered into a small number of representative colors. The color feature descriptor consists of the representative colors and their percentages in the image. An improved cumulative color histogram distance measure is defined for this descriptor. And also, we have developed an efficient edge detection technique as an optional feature to our retrieval system in order to surmount the weakness of color feature. During the query processing, both the features (color, edge information) could be integrated for image retrieval as well as a standalone entity, by specifying it in a certain proportion. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.1-12
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• 2008

This paper presents automatic moving object detection method using the rotating camera covering larger area with a single camera. The proposed method is based on the edge segment matching which robust to the dynamic environment with illumination change and background movement. The proposed algorithm presents an edge segment based background panorama image generation method minimizing the distortion due to image stitching, the background image generation method using Generalized Hough Transformation which can reliably register the current image to the panorama image overcoming the stitching distortions, the moving edge segment extraction method that overcome viewpoint difference and distortion. The experimental results show that the proposed method can detect correctly moving object under illumination change and camera vibration.