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

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.701-706
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• 2002

A set of color features has been efficiently used to measure the similarity of given images. However, the size of the color features is too large to implement an indexing scheme effectively. In this paper a new method is proposed to retrieve similar images using an interpolated color histogram. The idea is similar to the already reported methods that use the distributions of color histograms. The new method is different in that simplified color histograms decide the similarity between a query image and target images. In order to represent the distribution of the color histograms, the best order of interpolated polynomial has been simulated. After a histogram distribution is represented in a polynomial form, only a few number of polynomial coefficients are indexed and stored in a database as a color descriptor. The new method has been applied to real images and achieved satisfactory results.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.715-718
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• 2001

인터넷 문화 활성화에 따라, 새로이 제작된 멀티 미디어 컨텐츠의 부가가치가 높아지고 있으며, 저작물에 대한 도용 또한 문제시 되고 있다. 멀티미디어 매체 중에서 이미지는 큰 비중을 차지하고 있으며, 인터넷 상에서 도용된 이미지는 원본으로 부터 크기 확대 및 축소, 가로/세로비 변화, 문자 강제 색인 등의 형태로 변형되어 나타난다. 본 논문은 이와 같이 웹상에서 변형 도용된 이미지를 검색하기 위하여, MPEG-7 컬러 기술자인 Color Layout 기술자를 이용하여 모든 변형된 이미지를 검색하는 방법을 제안한다. 제안된 방법은 단순 변형 및 2 가지 이상이 혼합된 복합 변형된 도용 이미지들에 대해서도 검색이 가능하다. 정량적 평가를 위해 인위적으로 조작된 351 개의 이미지를 대상으로 MPEG-7 검색 성능 평가 지수인 ANM-RR (Average Normalized Modified Retrieval Rank)를 이용하여 효용성을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.211-227
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• 2011

Content Based Image Retrieval (CBIR) is an approach for retrieving similar images from an image database based on automatically-derived image features. The quality of a retrieval system depends on the features used to describe image content. In this paper, we propose an image clustering system that takes a database of images as input and clusters them using k-means clustering algorithm taking into consideration color, texture and shape features. Experimental results show that the combination of the three features brings about higher values of accuracy and precision.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.562-570
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• 2012

This paper proposes a robust object tracking algorithm using object features and on-line learning based particle filter for mobile robots. Mobile robots with a side-view camera have problems as camera jitter, illumination change, object shape variation and occlusion in variety environments. In order to overcome these problems, color histogram and HOG descriptor are fused for efficient representation of an object. Particle filter is used for robust object tracking with on-line learning method IPCA in non-linear environment. The validity of the proposed algorithm is revealed via experiments with DBs acquired in variety environment. The experiments show that the accuracy performance of particle filter using combined color and shape information associated with online learning (92.4 %) is more robust than that of particle filter using only color information (71.1 %) or particle filter using shape and color information without on-line learning (90.3 %).

• Proceedings of the Korean Information Science Society Conference
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• 1998.10a
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• pp.258-260
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• 1998

CPN(Colored Petri Net)은 시스템을 분석하고 설계하는 모델링 기법인 페트리넷의확장형으로서, 토큰에 color을 부여하여 자료흐름까지 고려할 수 있다. 이 연구에서 Estelle 로 기술된 프로토콜 명세를 Design /CPN에 적용가능한 CPN으로의 변환 방법을 제안하였다. 그리고 변환된 CPN을 Design /CPN에 입력하여 얻은 OG(Occurrence Graph)와 각 노드에 대한 내부 정보인 descriptor를 이용하여, 자료흐름이 고려된 보다 간편하고 효율적인 테스트 케이스를 생성하였다.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1479-1482
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• 2003

MPEG-21 Part 7(Digital Item Adaptation)은 멀티미디어컨텐츠를 사용자 환경 및 사용자 특성에 적응 적으로 활용/소비하기 위한 표준이다. 본 논문에서는, 영상컨텐츠의 적응적 컬러 재생에 관련하여 MPEG-21 DIA 내에서 표준화가 진행중인 조명환경 기술자(Descriptor)와 컬러 선호성 기술자를 소개하고 이들의 활용에 관해 논한다.

• Journal of Broadcast Engineering
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• v.8 no.1
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• pp.91-100
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• 2003

In this paper, to improve the retrieval Performance, an efficient combination of the MPEG-7 visual descriptors, such as the edge histogram descriptor (EHD), the color layout descriptor (CLD), and the homogeneous texture descriptor (HTD), is proposed in the framework of the relevance feedback approach. The EHD represents spatial distribution of edges in local image regions and it is considered as an important feature to represent the content of the image. The CLD specifies spatial distribution of colors and is widely used in image retrieval due to its simplicity and fast operation speed. The HTD describes precise statistical distribution of the image texture. Both the feature vector for the query image and the weighting factors among the combined descriptors are adaptively determined during the relevance feedback. Experimental results show that the proposed method improves the retrieval performance significantly tot natural images.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.164-174
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• 2015

In a real scenario, radiometric change has frequently occurred in the stereo image acquisition process using multiple cameras with geometric characteristics or moving a single camera because it has different camera parameters and illumination change. Conventional stereo matching algorithms have a difficulty in finding correct corresponding points because it is assumed that corresponding pixels have similar color values. In this paper, we present a new method based on the local descriptor reflecting intensity, gradient and texture information. Furthermore, an adaptive weight for local descriptor based on the entropy is applied to estimate correct corresponding points under radiometric variation. The proposed method is tested on Middlebury datasets with radiometric changes, and compared with state-of-the-art algorithms. Experimental result shows that the proposed scheme outperforms other comparison algorithms around 5% less matching error on average.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.237-243
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• 2014

In this paper, we propose a mobile image retrieval system which utilizes the mobile device's sensor information and enables running in a variety of the environments, and implement the system on Android platform. The proposed system deals with a new image descriptor using combination of the visual feature with EXIF attributes in the target of JPEG image, and image matching algorithm which is optimized to the mobile environments. Experiments are performed on the Android platform, and the experimental results revealed that the proposed algorithm exhibits a significant improved results with large image database.