• Journal of KIISE:Databases
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• v.35 no.4
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• pp.345-355
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• 2008

SIFT is popularly used in computer vision application such as object recognition, motion tracking, and 3D reconstruction among various shape descriptors. However, it is not easy to apply SIFT into the image similarity search as it is since it uses many high dimensional keypoint vectors. In this paper, we present a SIFT based image similarity search method using an edge image pyramid and an interesting region detection. The proposed method extracts keypoints, which is invariant to contrast, scale, and rotation of image, by using the edge image pyramid and removes many unnecessary keypoints from the image by using the hough transform. The proposed hough transform can detect objects of ellipse type so that it can be used to find interesting regions. Experimental results demonstrate that the retrieval performance of the proposed method is about 20% better than that of traditional SIFT in average recall.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.171-180
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• 2003

A content-based image retrieval(CBIR) system builds the image database using low-level features such as color, shape and texture and provides similar images that user wants to retrieve when the retrieval request occurs. What the user is interest in is a response time in consideration of the building time to build the index database and the response time to obtain the retrieval results from the query image. In a content-based image retrieval system, the similarity computing time comparing a query with images in database takes the most time in whole response time. In this paper, we propose the two-phase search method with the clustering technique of feature vector in order to minimize the similarity computing time. Experimental results show that this two-phase search method is 2-times faster than the conventional full-search method using original features of ail images in image database, while maintaining the same retrieval relevance as the conventional full-search method. And the proposed method is more effective as the number of images increases.

• Journal of Creative Information Culture
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• v.6 no.1
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• pp.41-48
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• 2020

In order to represent and process spatial data, hierarchical data structures such as a quadtree or a bintree are used. Various approaches for linearly representing the bintree have been proposed. S-Tree has the advantage of compressing the storage space by expressing binary region image data as a linear binary bit stream, but the higher the resolution of the image, the longer the length of the binary bit stream, the longer the storage space and the lower the search performance. In this paper, we construct a hierarchical structure of multiple separated bintrees with a full binary tree structure and express each bintree as two linear binary bit streams to reduce the range required for image search. It improves the overall search performance by performing a simple number conversion instead of searching directly the binary bit string path. Through the performance evaluation by the worst-case space-time complexity analysis, it was analyzed that the proposed method has better search performance and space efficiency than the previous one.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.311-312
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• 2007

This dissertation proposes a global search and a local search method to track the object in real-time. The global search recognizes a target object among the candidate objects through the entire image search, and the local search recognizes and track only the target object through the block search. This dissertation uses the object color and feature information to achieve fast object recognition. Finally we conducted an experiment for the object tracking system based on a pan/tilt structure.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.811-819
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• 2012

In this paper, we design searchable image encryption system to provide the privacy and authentication on streaming media based on cloud computing. The searchable encryption system is the matrix of searchable image encryption system by extending the streaming search from text search, the search of the streaming service is available, and supports personal privacy and authentication using encryption/decryption and CBIR technique. In simple simulation of post-cut and image keyword creation, we can verify the possibilities of the searchable image encryption system based on streaming service.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.645-648
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• 2002

본 논문에서는 비디오 압축에 이용되는 블록 기반 움직임 예측을 위하여 육각 패턴을 이용한 블록 정합 알고리즘을 제안한다. 제안하는 알고리즘은 기존의 3$\times$3 패턴을 이용한 BBGDS 알고리즘과 유사하게 계산 속도의 향상과 더불어 좀 더 강인한 움직임 예측을 할 수 있도록 패턴을 설계하였다. 제안하는 알고리즘을 바탕으로 적은 양의 탐색점(Search Point)을 이용하면서 확장된 탐색 영역(Search Area)을 이용할 수 있다. 제안한 알고리즘의 성능과 계산 속도의 향상이 실험 결과로 보여 진다.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.265-272
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• 2005

In this paper, we propose a technique which is speedily searching for correspondent points of two images using Voronoi-Distance, as an image registration method for feature based image mosaics. It extracts feature points in two images by the SUSAN corner detector, and then create not only the Voronoi Surface which has distance information among the feature points in the base image using a priority based Voronoi distance algorithm but also select the model area which has the maximum variance value of coordinates of the feature points in the model image. We propose a method for searching for the correspondent points in the Voronoi surface of the base image overlapped with the model area by use of the partitive search algorithm using queues. The feature of the method is that we can rapidly search for the correspondent points between adjacent images using the new Voronoi distance algorithm which has $O(width{\times}height{\times}logN)$ time complexity and the the partitive search algerian using queues which reduces the search range by a fourth at a time.

• Journal of the Ergonomics Society of Korea
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• v.31 no.6
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• pp.705-713
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• 2012

Objective: The aim of this study is to predict human visual target search using ACT-R cognitive architecture in real scene images. Background: Human uses both the method of bottom-up and top-down process at the same time using characteristics of image itself and knowledge about images. Modeling of human visual search also needs to include both processes. Method: In this study, visual target object search performance in real scene images was analyzed comparing experimental data and result of ACT-R model. 10 students participated in this experiment and the model was simulated ten times. This experiment was conducted in two conditions, indoor images and outdoor images. The ACT-R model considering the first saccade region through calculating the saliency map and spatial layout was established. Proposed model in this study used the guide of visual search and adopted visual search strategies according to the guide. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed ACT-R model is able to predict the human visual search process in real scene images using salience map and spatial layout. Application: This study is useful in conducting model-based evaluation in visual search, particularly in real images. Also, this study is able to adopt in diverse image processing program such as helper of the visually impaired.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.537-544
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• 2006

Image Search is one of the most exciting and fast growing research areas in the filed of multimedia technology. This paper conducts an empirical evaluation of color descriptor that uses the information of color distribution in color images, which is the most basic element for image search. With the experimental results, we observe that in the top 10% of precision, HSV, Daubechies 9/7 and 2 level decomposition have little better than others. Also histogram quadratic metrics outperform the Minkowski form distance metrics in similarity measurements, but spend more than 20 in computational times.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.95-114
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• 2010

Multimedia searching is an important activity on the Web, especially among the younger generation. The purpose of this study aims to examine college students’ multimedia information needs and searching on the Internet. While there is a clear pattern among students with respect to their multimedia uses, searching sources, relevance criteria and searching barriers, some differences exist especially according to searching of different multimedia types such as image, audio and video. For multimedia uses, information/data-focused uses are frequently found in image and video, while the use of audio is mainly for object-focused searches. As multimedia searching sources, audio and video files present a similar pattern of being high in media specific searching sources and low in generic search engines. Browsing through related blogs and homepages is an important part of searching for media files accounting for approximately 20% of total search for each media. The relevance criteria used by study participants when search for image files was primarily concerned with topicality while the contextual and media quality in the audio and video types are also considered important. Searching barriers for audio and video files are categorized into three broad aspects, including access and search quality, preview limitations and collection limitations, while obstacles for image files searching include access difficulties and low qualities of various collection.