• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.3 s.303
• /
• pp.73-80
• /
• 2005

Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.5 s.305
• /
• pp.1-10
• /
• 2005

Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.11a
• /
• pp.217-220
• /
• 2007

In this paper, we present a new anchor shot detection system which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) anchor shot detection module using a support vector data description. According to our computer experiments, the proposed system shows not only the comparable accuracy to the recent other results, but also more faster detection rate than others.

• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.341-344
• /
• 2000

본 논문에서는 복잡한 배경이나 조명 변화가 심한 영상에서도 피부영역을 정확하게 검출할 수 있는 피부영역 검출방법을 제안한다. 제안된 방법은 오프라인(off-line) 훈련과정과 온라인(on-line) 검출과정의 두 단계로 나누어진다. 훈련단계에서는 다양한 조명하에서 얻은 피부영상과 배경영상으로 구성된 훈련영상을 다차원의 열벡터로 표현하고 열벡터에 LDA(linear discriminant analysis)를 적용하여 선형변환된 특징벡터를 가지고 인덱싱 테이블을 생성한다. 검출단계에서는 카메라로 들어온 칼라영상을 여러 개의 조각영상으로 나누고 각각의 조각영상에 대하여 LDA를 적용하여 선형변환된 특징벡터를 구한다. 구해진 특징벡터를 미리 생성한 LDA 인덱싱 테이블에서 찾아 피부영역을 검출한다. 제안된 방법을 조명을 변화시킨 다양한 영상에 적용하여 실험한 결과 검출률이 상당히 우수함을 알 수 있었다.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.12
• /
• pp.1083-1087
• /
• 2005

As development of digital technology, many kinds of multimedia data are used variously and requirements for effective use by user are increasing. In order to transfer information fast and precisely what user wants, effective retrieval method is required. As existing multimedia data are impossible to apply the MPEG-1, MPEG-2 and MPEG-4 technologies which are aimed at compression, store and transmission. So MPEG-7 is introduced as a new technology for effective management and retrieval of multimedia data. In this paper, we extract content-based features using color descriptor among the MPEG-7 standardization visual descriptor, and reduce feature data applying PCA(Principal Components Analysis) technique. We model the cerebral cortex and hippocampal neural network in engineering domain, and team content-based feature vectors fast and apply the hippocampal neural network algorithm to compose of optimized feature. And then we present fast and precise retrieval effect when indexing and retrieving.

• Journal of Broadcast Engineering
• /
• v.7 no.3
• /
• pp.262-270
• /
• 2002

Although most image indexing schemes ate based on global image features, they have limited discrimination capability because they cannot capture local variations of the image. In this paper, we propose a new region-based image retrieval system that can extract important regions in the image using salient point extraction and image segmentation techniques. Our experimental results show that color and texture information in the region provide a significantly improved retrieval performances compared to the global feature extraction methods.

• Proceedings of the KIEE Conference
• /
• 2005.05a
• /
• pp.164-166
• /
• 2005

In this paper, using ranks of co-occurrence frequency about indices in neighboring pixels, we introduce a new re-indexing scheme for efficiency of index color image lossless compression. The proposed method is suitable for arithmetic coding because it has skewed distributions of small variance. Experimental results proved that the proposed method reduces the bit rates than other coding schemes, more specifically 15%, 54% and 12% for LZW algorithm of GIF, the plain arithmetic coding method and Zeng's scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.1
• /
• pp.127-135
• /
• 2009

This paper presents a new technique for corner shape based object retrieval from a database. The proposed feature matrix consists of values obtained through a neighborhood operation of detected corners. This results in a significant small size feature matrix compared to the algorithms using color features and thus is computationally very efficient. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. As the affine transformations preserve the co-linearity of points on a line and their intersection properties, the resulting corner features for image retrieval are robust to affine transformations. Furthermore, the corner features are invariant to noise. It is considered that the proposed algorithm will produce good results in combination with other algorithms in a way of incremental verification for similarity.

• International Journal of Contents
• /
• v.6 no.3
• /
• pp.5-9
• /
• 2010

To manage large database system with video, effective video indexing and retrieval are required. A large number of video retrieval algorithms have been presented for frame-wise user query or video content query, whereas a few video identification algorithms have been proposed for video sequence query. In this paper, we propose an effective video identification algorithm for video sequence query that employs the Cauchy function of histograms between successive frames and the modified Hausdorff distance. To effectively match the video sequences with a low computational load, we make use of the key frames extracted by the cumulative Cauchy function and compare the set of key frames using the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed algorithm for video identification yields remarkably higher performance than conventional algorithms such as Euclidean metric, and directed divergence methods.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.1
• /
• pp.133-138
• /
• 2008

In this paper, we propose a novel anchor shot detection system, named to MASD (Multi-phase Anchor Shot Detection), which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) one class SVM module for determining the anchor shots using a support vector data description. Besides the qualitative analysis, our experiments validate that the proposed system shows not only the comparable accuracy to the recently developed methods, but also more faster detection rate than those of others.