• Journal of the Korea Society of Computer and Information
• /
• v.11 no.4 s.42
• /
• pp.147-154
• /
• 2006

Effective and efficient representation of color features of multiple video frames is an important vet challenging task for visual information management systems. This paper Proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web. For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combine the RGB color histogram with the X2 (Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing. This system involves the video editing and retrieval function of a VCR's. Three elements that are the date, the need and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• KSCI Review
• /
• v.15 no.1
• /
• pp.203-207
• /
• 2007

본 논문에서는 비디오의 분할을 위하여 먼저 기존에 제안되었던 차이 값 추출방법들의 단점들을 극복하고 장점을 최대한 활용할 수 있으며 급진적 장면전환부터 점진적 장면전환까지 모두 예측할 수 있는 강건하고 복합적인 차이 값 추출방법에 대해서 제안한다. 이 방법은 지역적 $X^2$-테스트로서 기존의 컬러 히스토그램과 $X^2$-테스트를 결합한 방법이다. 본 논문을 위하여 기존의 히스토그램 기반 알고리즘과 비교하여 좋은 성능을 보여주는 $X^2$-테스트를 변형하였고, 컬러 값의 세분화 작업에 따른 검출효과를 높이기 위하여 명암도 등급에 따른 가중치를 적용한 지역적 $X^2$-테스트를 이용하였다. 이 방법은 복잡하고 다양한 시세계의 영상 변화를 가장 일반적이고 표준화된 방법으로 분석하고 분할하며 표현할 수 있는 방법이다. 기존의 $X^2$-테스트와 제안된 지역적 $X^2$-테스트 방법의 비교는 실험을 통해 입증되었다.

• 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.13 no.6
• /
• pp.147-154
• /
• 2008

First, this paper compute difference value between frames using the composed method of $X^2$ histogram and color histogram and the normalization. Next, cluster representative frame was decided by using the clustering for distance and the k-mean grouping. Finally, representative frame of group was decided by using the likelihood ratio. Proposed method can be known by experiment as outstanding of detection rather than other methods, due to computing of difference value, clustering and grouping, and detecting of representative frame.

• Journal of the Korean Wood Science and Technology
• /
• v.26 no.2
• /
• pp.29-37
• /
• 1998

An image analysis program with the function of measuring various quantitative characteristics in the transverse surface of wood was developed using Delphi 2.0. Data on pore characteristics (conditions for image processing, proportion of pores in relationship to other elements, tangential diameter, area, tangential and radial diameter, x and y coordinates of pore center, and geometric coefficients) were saved in text file format. In addition, the pore area histogram in the tangential and radial directions was saved as a BMP (bitmap) type file. Analyses indicated that quantitative characteristics such as the relative radial distribution of pores in a growth ring, pore tangential area histogram, and proportion of pore in lumen area appear to be useful in separating four diffuse-porous woods and four ring-porous woods on the species level.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
• /
• v.29 no.2
• /
• pp.417-422
• /
• 1999

Purpose : The aim of this study was to assess the validity of standard deviation of gray scale histogram in digital subtraction radiography as a test parameter for superimposition error. Materials and Methods : Twenty periapical radiographs were used as baseline images and they were copied to exclude the influence of exposure geomety and contrast differences. These subsequent images were linearly displaced by 0.1-0.5 mm in the x-. y- and xy-directions, rotated by 0.5-3° and distorted by angular contraction of 1-5° in x- and y-axis before subtraction. The standard deviations of gray levels in the subtraction images were obtained and paired t-tests were performed. Pearson correlation coefficients(r) were calculated between the standard deviations and the superimposition errors. Results : Linear displacement showed high correlation coefficients of 0.997, 0.997 and 0.995 in x-. y- and xy-axis respectively. Statistically significant different standard deviation existed among all linearly displaced groups(p<0.05). Distortion showed relatively low correlation coefficients of 0.982 and 0.959 in x- and y-axis. The standard deviations between the two distortion groups were statistically significant different(p<0.05). Conclusion : Standard deviation of gray level distribution in digital subtraction images is satisfactory but not perfect similarity measure to assess the superimposition errors.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2015.01a
• /
• pp.45-46
• /
• 2015

본 논문에서는 엘리베이터 내에서의 폭행 장면을 효율적으로 추출하기 위해 컬러-$x^2$ 히스토그램을 이용하였다. 컬러-$x^2$ 히스토그램은 컬러히스토그램의 장점과 $x^2$ 히스토그램의 장점을 결합한 추출 방법이다. 또한 기존의 컬러-$x^2$ 히스토그램을 이용하여 키 프레임을 찾아내기 위해 임계값을 찾아낼 때, 실제 폭행 장면 인지 아닌지를 판별하는 확률을 높이기 위해 20개의 샘플영상을 이용하여 통계적인 판단을 이용하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2005.11a
• /
• pp.189-192
• /
• 2005

비디오 분할의 목적은 같은 내용들을 가지는 프레임들의 순서를 표현하는 각 샷의 비디오 순서 분할을 위한 것이다. 그리고 색인에 대한 각 샷으로부터 키 프레임을 선택한다. 존재하는 비디오 분할 방법들은 2가지 그룹들로 분류될 수 있다. 먼저 경계값이 할당되어야만 하는 샷 전환 검출(SCD) 접근과 클러스터 수의 사전 지식이 요구되는 클러스터 접근이다. 본 논문에서는 컬러-$x^2$명도 히스토그램 기반 FCM(fuzzy c-means) 클러스터링 알고리즘을 사용하는 비디오 분할 방법을 제안하였다. 이 알고리즘은 앞에서 기술한 2가지 접근의 혼합이다. 그리고 이것은 두 가지 접근들의 결점을 극복하도록 설계 되었다. 실험 결과들은 컬러-$x^2$명도 히스토그램 기반 FCM 클러스링 알고리즘이 강건하고 비디오 시퀀스들의 다양한 형태들에 응용할 수 있다고 제안한다.

• Journal of Internet Computing and Services
• /
• v.3 no.2
• /
• pp.69-77
• /
• 2002

Recently, Digital video is one of the important information media delivered on the Internet and playing an increasingly important role in multimedia. This paper proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web, For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combines the RGB color histogram with the $x^2$(Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing, This system involves the video editing and retrieval function of a VCR's, Three elements that are the date, the field and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
• /
• v.25 no.2
• /
• pp.375-387
• /
• 1995

The purpose of this study was to quantitatively evaluated experimental tooth root resorption for digital radiography. For this study, experimentally three root sites were used, and radiograms were taken with standardized apparatus. Digital imaging system were consisted of NEC PC-980l(computer), TRINITRON(monitor), SONY XC-711 CCD camera. The display monitor had a resolution of 512X512 pixels. The obtained results were as follows: 1. In the difference of the four X-ray film of the contrast correction, the contrast difference was one gray scale variation at mean value. 2. Viewing of the view box of the periapical radiographs, experimental tooth root resorption of the periapical area of the first premolar, middle of mesial surface of the first molar mesial root, middle of lingual surface of the first molar distal root were recognized by increased diameter. 3. On the analysis by histogram, the periapical area of the first premolar, the middle of mesial surface of the first molar mesial root were each recognized tooth root resorption of the 5,6,7 pixel, 2,4,5 pixel by increased diameter. 4. On the analysis by histogram, the middle of lingual surface of the first molar distal root was each recognized tooth root resorption of the none, 3,6 pixel by increased diameter.