• Journal of Korea Multimedia Society
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• 제18권10호
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• pp.1180-1188
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• 2015

In this paper, a parallel cell contour line extraction algorithm using CUDA, which has no inner contour lines, is proposed. The contour of a cell is very important in a cell image analysis. It could be obtained by a conventional serial contour tracing algorithm or parallel morphology operation. However, the cell image has various damages in acquisition or dyeing process. They could be turn into several inner contours, which make a cell image analysis difficult. The proposed algorithm introduces a min-max coordinates table into each CUDA thread block, and removes the inner contour in parallel. It is 4.1 to 7.6 times faster than a conventional serial contour tracing algorithm.

• Journal of the Optical Society of Korea
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• 제6권4호
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• pp.143-149
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• 2002

In this paper, we present an algorithm for synthesizing intermediate views from a stereoscopic pair of images. Syntheses of intermediate images allows one to realize a more comfortable the 3D display system. The proposed method is based on block matching, which is not ordinarily used. The contour information is used for a block decision. In order to find an equivalent (or corresponding) block, there are two steps: "matching of contour-to-original image" and "matching of contour-to-contour image" methods. "Matching of contour-to-contour image" uses both left and right contour images. This block matching method allows us to find the corresponding block in spite of different block sizes. Experimental results illustrate the performance of the proposed technique and we obtained a high quality image of more than 31 dB PSNR.image of more than 31 dB PSNR.

• Proceedings of the IEEK Conference
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.915-918
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• 1998

Region based coding consistsof image segmentation contour and texture coding. Contour coding techniques can be classified into contour or shape-oriented approaches. In this paper, geodesic skeleton based on shape-oriented approach is used for contour coding. Efficient application of geodesic skeleton for contour coding based on the characteristics of regions in segmented image will be discussed.

• Journal of Korea Multimedia Society
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• 제20권5호
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• pp.740-747
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• 2017

A fast cell contour extraction method using CUDA parallel processing technique is presented. The cell contour extraction is one of important processes to analyze cell information in pathology. However, conventional sequential contour extraction methods are slow for a huge high-resolution medical image, so they are not adequate to use in the field. We developed a parallel morphology operation algorithm to extract cell contour more quickly. The algorithm can create an inner contour and fail to extract the contour from the concave part of the cell. We solved these problems by subdividing the contour extraction process into four steps: morphology operation, labeling, positioning and contour extraction. Experimental results show that the proposed method is four times faster than the conventional one.

• International Journal of Control, Automation, and Systems
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• 제2권1호
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• pp.100-106
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• 2004

In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제4권1호
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• pp.123-130
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• 2000

In this paper, we propose an extracting method of moving object contour using active contour model from image sequences acquired by fixed camera. We use an adaptive background model for robust processing in surrounding conditions. Object segmentation model detects pixels thresholded from local difference image between background and current image and extracts connected regions. Noises in boundary area of moving object we eliminated by morphological filter. The contour of segmented object is corrected by using active contour model for extracting accurate boundary of moving object. We apply the proposed method to highway image sequences and show the results of simulation.

• Journal of the Institute of Convergence Signal Processing
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• 제3권4호
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• pp.7-16
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• 2002

En this paper, we propose the algorithm that has analyzed the map Information automatically to extract the contour lines and numbers, symbols from the map image. After converting the input image to binary one, thinned image is obtained by thinning algorithm. The contour elements in the thinned image are classified and the classified elements are analyzed to automatically classify the numbers from symbols. Finally, the broken parts are restored by reconstruction algorithm. The performance of proposed algorithm is verified through the simulation. The proposed one has good performance.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

• Journal of the Korea Society of Computer and Information
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• 제3권1호
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• pp.81-94
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• 1998

In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes". Snakes is a model which defines the contour of image energy. It also can find the contour of object by minimizing these energy functions. The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initialization. and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of 8$\times$8 size at each contour point consisting Snakes in order to solve these problems. The method offered in this paper is applied to extract the contour of original image and cup image added to gaussian noise. By tracking the face using this offered method, it is applied to virtual reality and motion tracking. tracking.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1462-1467
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• 2013

A pseudo 480-Hz drive method has been proposed to reduce the dynamic false contour noise that occurs on flat panel displays with displaying grayscale image in the digital mode, such as plasma display panels. The proposed method makes the image movements nearly continuous by rearranging the 8-bit image data displayed for 1 TV field into 8 subfields. The position of the image data rearranged in subfields has been optimized on the basis of the speed of the moving image by computer simulations for the dynamic false contour noise. It is verified that a significant reduction in the dynamic false contour noise is achieved with the proposed method as compared to the conventional noise reduction technologies. Moreover, to reduce the noise in digital mode displays, the proposed technology requires only 8 subfields. Therefore, there is no reduction in the brightness of the image.