• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.166-173
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• 2005

Preserving image features, edges and details in the process of impulsive noise filtering is an important problem. To avoid image blurring, only corrupted pixels must be filtered. In this paper, we propose an effective impulse noise detection method using Self-Organizing Neural Network(SONN) which applies median filter selectively for removing random-valued impulse noises while preserving image features, edges and details. Using a $3\times3$ window, we obtain useful local features with which impulse noise patterns are classified. SONN is trained with sample image patterns and each pixel pattern is classified by its local information in the image. The results of the experiments with various images which are the noise range of $5-15\%$ show that our method performs better than other methods which use multiple threshold values for impulse noise detection.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.197-202
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• 2016

This paper suggested that medical image database construction technique that generated and recognized from variable medical device and professional medical experts for the formalization and pattern extraction from informal medical images. And then we transformed informal image characteristics to digital data, and generated the meaningful pattern matching informations. Through this experienced works, so many related researchers can easily access the medical images database and use this formalized image informations on the variable fields.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.61-69
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• 1994

For distortion-invariant recognition of Korean characters, a holographic implementation of an optical associative memory system is proposed. The structure of the proposed system is a single-layer neural network employing interconneclion matrix, thresholding and feedback. To provide the interconnection matrix, we use two CGII's which are placed on intermcdiate plane of cascaded Vander Lugt corrclators to form an optical memory loop. The holographic correlator stores reference images in a hologram and retrives them in a coherently illuminated feedback loop. An input image which maybe noisy or incomplete, is applicd to the system and simultaneously correlated optically with all of the stord images. These correlations are throsholed and fed back to the input, where the strongest correlation reinforces the input image. The enhanced image passes arround the loop repeatedly, approaching the stored image more closely on each pass until the system stabilizes on the desired image. The computer simulation results show that the proposed Korean Character recognition algorithm has high discrimination capability and noise immunity.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1678-1680
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• 2002

Stereo matching technique is used in many practical fields like satellite image analysis and computer vision. In this paper, we suggest a method to extract a target object image from a complicated background. For example, human face image can be extracted from random background. This method can be applied to computer vision such as security system, dressing simulation by use of extracted human face, 3D modeling, and security system. Many researches about stereo matching have been performed. Conventional approaches can be categorized into area-based and feature-based method. In this paper, we start from area-based method and apply area tracking using scanning window. Coarse depth information is used for area merging process using area searching data. Finally, we produce a target object image.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.959-961
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• 1995

The objective of most image proccessing applications is to extract meaningful information from one or more pictures. It is accomplished efficiently using neural networks, which is used in image classification and image recognition. In neural networks, background and meaningful information are processed with same weight in input layer. In this paper, we propose the image classification method using neural networks, especially EBP(Error Back Propagation). Preprocessing is needed. In preprocessing, background is compressed and meaningful information is emphasized. We use the quadtree approach, which is a hierarchical data structure based on a regular decomposition of space.

• Journal of the Semiconductor & Display Technology
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• v.9 no.4
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• pp.57-61
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• 2010

The wavelet transform was adopted as the transform for JPEG2000. However, wavelet has weakness about smoothness along the contours and limited directional information. So we use to other transform, called contourlet transform in compression. Objective quality assessment methods currently used Peak signal to noise Ratio(PSNR). But that is not very well matched to perceived visual quality. So new image quality assessment is required. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. In addition we evaluated compression image quality using PSNR and SSIM. Finally contourlet transform has a good result about images with smooth contours and SSIM is good method for image evaluation compared to PSNR.

• Journal of the Optical Society of Korea
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• v.13 no.1
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• pp.139-145
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• 2009

Computational integral imaging (CII) is a new method for 3D imaging and visualization. However, it suffers from seriously poor image quality of the reconstructed image as the reconstructed image plane increases. In this paper, to overcome this problem, we propose a CII method based on a smart pixel mapping (SPM) technique for partially occluded 3D object recognition, in which the object to be recognized is located at far distance from the lenslet array. In the SPM-based CII, the use of SPM moves a far 3D object toward the near lenslet array and then improves the image quality of the reconstructed image. To show the usefulness of the proposed method, we carry out some experiments for occluded objects and present the experimental results.

• Journal of Industrial Technology
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• v.18
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• pp.17-25
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• 1998

Recently, there are a lot of studies to use a satellite image data in order to investigate a simultaneous change of a wide range area as a lake. However, many cases of a water quality research occur as problem when we try to extract the water quality factors from the satellite image data, because of the atmosphere scattering exert as bad influence on a result of analysis. In this study, and attempt was made to select the relative atmospheric correction method for the water quality factors extraction from the satellite image data. And also, the time-series analysis of the water quality factors extraction from the satellite image data. And also, the time-series analysis of the water quality factors was performed by using the multi-temporal image data.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.145-156
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• 2003

This paper for real time object tracking in this treatise detect histogram analysis that is accumulation value of binary conversion density and edge information and body that move by real time use of difference Image techniques and proposed method to object tracking. Firstly, we extract edge that can reduce quantity of data keeping information about form of input image in object detection. Object is extracted by performing difference image and binarization in edge image. Area of detected object is determined by threshold value that divide sum of horizontal accumulation value about binary conversion density by value that add horizontalityㆍverticality maximum accumulation value. Object is tracked by comparing similarity with object that is detected in previous frame and present frame. As experiment result, proposed algorithm could improve the object detection speed, and could track object by real time and could track local movement.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.1
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• pp.57-62
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• 1994

In this paper, a system for measuring of treeing degradation in organic dielectric material by using image processing technics, is discussed. Traditionally, treeing is measured by visual method. It made difficulty to understanding for features and changes in the configlEation of the tree growth. Using image processing system, it is made to describe the characters of the tree growth, specially length of tree and area of treeing degradation. From this image processing and visual measurement, the similar results were made, an automatic measurement system was made for configuration of the tree growth.