• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.346-349
• /
• 2017

Digital image processing is widely used in a variety of areas, and noise elimination is used as the preprocessing in all the image processing processes. Degradation is occurred in the image data due to multiple reasons. Degradation is to add the noise in the image signal, and salt and pepper noise is the representative one to cause degradation. Therefore, image restoration algorithm was proposed to process with histogram weight filter and median filter by the noise density of local mask to restore the damaged image in the salt and pepper noise environment, in this article. In addition, it was compared with the existing methods using peak signal to noise ratio(PSNR) as the objective determination factor of improvement effect.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.1
• /
• pp.87-92
• /
• 2011

Server overload is directly proportional to requested image data size in a image processing. If request data are increase then system is overloaded in a image processing system. For the reduce of server bottle neck, we will be able to consider a distributed processing. Simple distributed processing system can solve server bottleneck and system overload but high cost system requirements. In this paper, Proposes a new distributed image processing system. Object activation technology are being grafted on to simple distributed processing system. It can optimize the user of system resources and can reuse idle system resources in network.

• Journal of Satellite, Information and Communications
• /
• v.9 no.4
• /
• pp.32-37
• /
• 2014

The panorama is a good alternative to overcome narrow FOV under study in robot vision, stereo camera and panorama image registration and modeling. The panorama can materialize view with angles wider than human view and provide realistic space which make feeling of being on the scene based on realism. If we use all correspondence, it is too difficult to find strong features and correspondences and assume accurate homography matrix in geographic changes in images as load of calculation increases. Accordingly, we used SURF algorithm to estimate overlapping areas with high similarity by comparing and analyzing the input images' histograms and to detect features. And we solved the problem of input order so we can make panorama by input images without order.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.3
• /
• pp.167-172
• /
• 2006

An image retrieval system retrieves and offers same of similar image based on various features of image. This paper present a brand image retrieval system based on color and shape of image. We use the image for a color information by dividing into the area and extracting the area color distribution histogram. We use for the shape information by preprocessing of the boundary extraction, the centroid extraction, angular sampling etc. and calculating of the sum of the distance from the centroid to the boundary, the standard deviation, and the rate of long axis to short axis. We accomplish the retrieval through a similarity measurement by using the color and shape information which is extracted in this way.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.1
• /
• pp.507-515
• /
• 2015

This paper suggests 6 cases of TFA parameters algorithm(Mean, VA, RS, SKEW, UN, EN) to search for the detection of recognition rates regarding breast disease using CAD on ultrasound images. Of the patients who visited a university hospital in Busan city from August 2013 to January 2014, 90 cases of breast ultrasound images based on the findings in breast US and pathology were selected. $50{\times}50$ pixel size ROI was selected from the breast US images. After pre-processing histogram equalization of the acquired test images(negative, benign, malignancy), we calculated results of TFA algorithm using MATLAB. As a result, in the TFA parameters suggested, the disease recognition rates for negative and malignancy was as high as 100%, and negative and benign was approximately 83~96% for the Mean, SKEW, UN, and EN. Therefore, there is the possibility of auto diagnosis as a pre-processing step for a screening test on breast disease. A additional study of the suggested algorithm and the responsibility and reproducibility for various clinical cases will determine the practical CAD and it might be possible to apply this technique to range of ultrasound images.

• Journal of Internet Computing and Services
• /
• v.16 no.1
• /
• pp.29-37
• /
• 2015

In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.

• Journal of Korea Multimedia Society
• /
• v.5 no.5
• /
• pp.505-514
• /
• 2002

In this Paper, we propose a method of content-based image classification using neural network. The images for classification ate object images that can be divided into foreground and background. To deal with the object images efficiently, object region is extracted with a region segmentation technique in the preprocessing step. Features for the classification are texture and shape features extracted from wavelet transformed image. The neural network classifier is constructed with the extracted features and the back-propagation learning algorithm. Among the various texture features, the diagonal moment was more effective. A test with 300 training data and 300 test data composed of 10 images from each of 30 classes shows correct classification rates of 72.3% and 67%, respectively.

• Journal of Biomedical Engineering Research
• /
• v.20 no.3
• /
• pp.283-290
• /
• 1999

Because MR(Magnetic Resonance) slice images have much information of functions about body organs, it is very effeclive for diagnoses lo analyze and visualize MR slice images. A visuahzation process is composed of medical image acquisition, preprocessmg, segmentation, inlerpolation, rendering. Segmentation and interpolation among thenl ,1re currenl hot topics because of MR slice image imperfections. This paper proposes a method for segmentalion, mlerpolation respectively and addresses 3 D-visualizmg of a head. We segmented head tissues uomg otructural knowledge of head studied by clinical experiments sequentially. We improved the dynamic elastic inlerpolation to Utilize in concave conlour. We compared the proposed segmentation method and the interpolation method with other methods.

• Journal of IKEEE
• /
• v.14 no.4
• /
• pp.332-338
• /
• 2010

Usually, mage feature extraction methods are performed as a pre-processing step in many applications including image retrieval, object recognition, and image indexing. Especially, in the image texture analysis, texture feature extraction methods attempt to increase texture contrast to make it easier to extract the texture features from the image. One of the distinct textures in microscopic skin image is the wrinkle, and its features could provide various useful information for the age-related applications. In this paper, we propose a scheme to extract age-related features from the skin images and improve its accuracy in the skin age estimation.

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.9
• /
• pp.237-246
• /
• 2016

DIBR (Depth Image Based Rendering) is a multimedia technology that generates the virtual multi-view images using a color image and a depth image, and it is used for creating glasses-less 3-dimensional display contents. This research describes the effect of depth accuracy about the objective quality of DIBR-based multi-view images. It first evaluated the minimum depth quantization bit that enables the minimum distortion so that people cannot recognize the quality degradation. It then presented the comparative analysis of non-uniform domain-division quantization versus regular linear quantization to find out how effectively express the accuracy of the depth information in same quantization levels according to scene properties.