• Journal of Korea Multimedia Society
• /
• v.14 no.10
• /
• pp.1252-1261
• /
• 2011

In this paper, we propose the comparison method of pattern similarity for video segmentation algorithm. The shot boundary type is categorized as 2 types, abrupt change and gradual change. The representative examples of gradual change are dissolve, fade-in, fade-out or wipe transition. The proposed method consider the problem to detect shot boundary as 2-class problem. We concentrated if the shot boundary event happens or not. It is essential to define similarity between frames for shot boundary detection. We proposed 2 similarity measures, within similarity and between similarity. The within similarity is defined by feature comparison between frames belong to same shot. The between similarity is defined by feature comparison between frames belong to different scene. Finally we calculated the statistical patterns comparison between the within similarity and between similarity. Because this measure is robust to flash light or object movement, our proposed algorithm make contribution towards reducing false positive rate. We employed color histogram and mean of sub-block on frame image as frame feature. We performed the experimental evaluation with video dataset including set of TREC-2001 and TREC-2002. The proposed algorithm shows the performance, 91.84% recall and 86.43% precision in experimental circumstance.

• Journal of Internet Computing and Services
• /
• v.16 no.1
• /
• pp.39-46
• /
• 2015

This paper presents an automatic method to detect and count the cells from microorganism images based on mobile environments. Cell counting is an important process in the field of biological and pathological image analysis. In the past, cell counting is done manually, which is known as tedious and time consuming process. Moreover, the manual cell counting can lead inconsistent and imprecise results. Therefore, it is necessary to make an automatic method to detect and count cells from biological images to obtain accurate and consistent results. The proposed multi-step cell counting method automatically segments the cells from the image of cultivated microorganism and labels the cells by utilizing topological analysis of the segmented cells. To improve the accuracy of the cell counting, we adopt watershed algorithm in separating agglomerated cells from each other and morphological operation in enhancing the individual cell object from the image. The system is developed by considering the availability in mobile environments. Therefore, the cell images can be obtained by a mobile phone and the processed statistical data of microorganism can be delivered by mobile devices in ubiquitous smart space. From the experiments, by comparing the results between manual and the proposed automatic cell counting we can prove the efficiency of the developed system.

• Journal of IKEEE
• /
• v.21 no.4
• /
• pp.412-415
• /
• 2017

In this paper, we propose a multi license plate recognition system using high resolution $360^{\circ}$ omnidirectional IP camera. The proposed system consists of a planar division part of $360^{\circ}$ circular image and a multi license plate recognition part. The planar division part of the $360^{\circ}$ circular image are divided into a planar image with enhanced image quality through processes such as circular image acquisition, circular image segmentation, conversion to plane image, pixel correction using color interpolation, color correction and edge correction in a high resolution $360^{\circ}$ omnidirectional IP Camera. Multi license plate recognition part is through the multi-plate extraction candidate region, a multi-plate candidate area normalized and restore, multiple license plate number, character recognition using a neural network in the process of recognizing a multi-planar imaging plates. In order to evaluate the multi license plate recognition system using the proposed high resolution $360^{\circ}$ omnidirectional IP camera, we experimented with a specialist in the operation of intelligent parking control system, and 97.8% of high plate recognition rate was confirmed.

• 한국HCI학회:학술대회논문집
• /
• 2008.02b
• /
• pp.298-303
• /
• 2008

Watching a program on IPTV among the numerous choices from the internet requires a burden of searching and browsing for a favorite one. This paper introduces a new concept called Mosaic Map and presents how it provides preview information of image map links to other programs. In Mosaic Map the pixels in the still image are used both as shading the background and as thumbnails which can link up with other programs. This kind of contextualized preview of choices can help IPTV users to associate the image with related programs without making visual saccades between watching IPTV and browsing many choices. The experiments showed that the Mosaic Map reduces the time to complete search and browsing, comparing to the legacy menu and web search.

• Journal of Korea Multimedia Society
• /
• v.15 no.9
• /
• pp.1149-1155
• /
• 2012

In this paper, we propose cause diagnosis method of semiconductor defects from semiconductor industrial images. Our method constructs feature database (DB) of defect images. Then, defect and input images are subdivided by uniform block. And the block similarity is measured using histogram kai-square distance after color histogram calculation. Then, searched blocks in each image are merged into connected objects using clustering. Finally, the most similar defect image from feature DB is searched with the defect cause by measuring cluster similarity based on features of each cluster. Our method was validated by calculating the search accuracy of n output images having high similarity. With n = 1, 2, 3, the search accuracy was measured to be 100% regardless of defect categories. Our method could be used for the industrial applications.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.3
• /
• pp.193-201
• /
• 2006

This paper presents a method that allows for detection of all rapid and gradual scene changes. The method features a combination of the current color histogram and the local $X^{2}-test$. For the purpose of this paper, the $X^{2}-test$ scheme outperforming existing histogram-based algorithms was transformed, and a local $X^{2}-test$ in which weights were applied in accordance with the degree of brightness was used to increase detection efficiency in the segmentation of color values. This Method allows for analysis and segmentation of complex time-varying images in the most general and standardized manner possible Experiments were performed to compare the proposed local $X^{2}-test$ method with the current $X^{2}-test$ method.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.123-131
• /
• 2008

In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of one's health like the physiological and the clinicopathological changes of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition a lot. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue region from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmenting, detecting the edge with a local minimum over a shading area from the structure of a tongue, correcting local minima or detecting the edge with the greatest color difference, selecting one edge to correspond to a tongue shape, and smoothing edges, where preprocessing consists of down-sampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue. Finally, the systematic procedure separated only a tongue region from a face image with a tongue, which was obtained from a digital tongue diagnosis system. Oriental medical doctors' evaluation for the results illustrated that the segmented region excluding a non-tongue region provides important information for the accurate diagnosis. The proposed method can be used for an objective and standardized diagnosis and for an u-Healthcare system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.801-804
• /
• 2013

We propose a new tongue examination model according to the taste division of tongue. The proposed sytem consists of image acquisition, region segmentation, color distribution analysis and abnormality decision of tongue. Tongue DB which is classified into abnormality is constructed with tongue images captured from oriental medicine hospital inpatients. We divided 4 basic taste(bitter, sweet, salty and sour) regions and performed color distribution analysis targeting each region under HSI(Hue Saturation Intensity) color model. To minimize the influence of illumination, the histograms of H and S components only except I are utilized. The abnormality of taste regions each by comparing the proposed diagnosis model with diagnosis results by a doctor of oriental medicine. We confirmed the 87.5% of classification results of abnormality by proposed algorithm is coincide with the doctor's results.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.677-680
• /
• 2001

본 논문에서는 컬러 장치들간에 색을 일치시키기 위하여 휘도 대비와 채도 향상을 고려한 원형 색역 사상(circular shape-based gamut mapping)방법을 제안하였다. 서로 다른 장치들간에 색역을 일치시키기 위해 장치 독립적이고 균등 색 공간인 CIELAB값으로 변환하여 색역 사상을 수행하였다. 인간 시각에 상대적으로 민감한 특성을 가지는 휘도 성분을 JND(just noticeable difference)에 기반해 분할하고, 이를 기점으로 색역을 원의 형태로 나눈다. 이렇게 나뉜 색역은 사상의 방향성을 결정하는 기본 단위로 사용되어, 이들 영역을 기점으로 영역 대 영역별 사상 방법을 사용하였다. 제안한 색역 사상 방법을 모니터와 프린터간에 적용한 결과 보다 선명하고 휘도 대비가 높은 영상을 얻을 수 있었다.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.6
• /
• pp.1183-1189
• /
• 2011

In this study, we propose the unsupervised image segmentation algorithm to estimate dental plaque accumulations on digital imaging with methylene blue disclosed plaque. With this aim, RGB color plane is mapped into HSI coordinates and the circular histogram of Hue is reconstructed by applying Otsu's threshold level. The histogram distribution on Saturation features is also analyzed by maximizing the variance between a plaque candidate and non-plaque one. The dental plaque regions are resolved by applying the composite decision logics based on the threshold level of Hue and Saturation.