• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2270-2277
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• 2016

In modern society, creation and distribution of multimedia contents is being actively conducted. These multimedia information have come out the enormous amount daily, the amount of data is also large enough it can't be compared with past text information. Since it has been increased for a need of the method to efficiently store multimedia information and to easily search the information, various methods associated therewith have been actively studied. In particular, image search methods for finding what you want from the video database or multiple sequential images, have attracted attention as a new field of image processing. Image retrieval method to be implemented in this paper, utilizes the attribute of corner patches based on the corner points of the object, for providing a new method of efficient and robust image search. After detecting the edge of the object within the image, the straight lines using a Hough transformation is extracted. A corner patches is formed by defining the extracted intersection of the straight line as a corner point. After configuring the feature vectors with patches rearranged, the similarity between images in the database is measured. Finally, for an accurate comparison between the proposed algorithm and existing algorithms, the recall precision rate, which has been widely used in content-based image retrieval was used to measure the performance evaluation. For the image used in the experiment, it was confirmed that the image is detected more accurately in the proposed method than the conventional image retrieval methods.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.867-870
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• 1998

Video data is usually stored in a compressed format in order to reduce the storage space. For efficient browsing, searching, and retrieval of compressed video sequences, size-reduced images (or DC images which are formed with block DC coefficients) are generally preferred to avoid unnecessary computational complexity. In this paper, we propose a DC image extraction scheme appropriate for scene analysis and efficient browsing of compressed video sequences. The proposed algorithm utilizes predicted low frequency AC coefficients to achieve better approximation and to reduce the error drift. Due to the AC prediction based on a quadratic surface model, the proposed scheme requires no additional memory compared with the previous zero-order or first-order approximation scheme. Simulation results show that the proposed scheme achieves better subjective and objective quality with minor additional operations.

• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1134-1141
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• 2005

With ever more popularity of video web-publishing, popular content is being compressed, reformatted and modified, resulting in excessive content duplication. Such overlapped data can cause problem of search speed and rate of searching. However, duplicated data on other site can provide alternatives while specific site cause problem. This paper proposes the efficient method, for retrieving. similar video data in large database. In this research we have used the method to compare summarized video image instead of the raw video data, and detected similar videos through clustering in that dimension feature vector through PCA(principle component analysis). We show that our proposed method is efficient and accurate through our experiment.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.152-157
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• 2010

The development of computer and internet has introduced various types of media - such as, image, audio, video, and voice - to the traditional text-based information. However, most of the information retrieval systems are based only on text, which results in the absence of ability to use available information. By utilizing the available media, one can improve the performance of search system, which is commonly called content-based retrieval and content-based image retrieval system specifically tries to incorporate the analysis of images into search systems. In this paper, a content-based image retrieval system using HSI color space, ART2 algorithm, and SOM algorithm is introduced. First, images are analyzed in the HSI color space to generate several sets of features describing the images and an SOM algorithm is used to provide candidates of training features to a user. The features that are selected by a user are fed to the training part of a search system, which uses an ART2 algorithm. The proposed system can handle the case in which an image belongs to several groups and showed better performance than other systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.8-15
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• 2007

Recently, it is important to process multimedia data efficiently. Especially, in case of retrieval of multimedia information, technique of user interface and retrieval technique are necessary. This paper proposes a new technique which detects cuts effectively in compressed image information by MPEG. A cut is a turning point of scenes. The cut-detection is the basic work and the first-step for video indexing and retrieval. Existing methods have a weak point that they detect wrong cuts according to change of a screen such as fast motion of an object, movement of a camera and a flash. Because they compare between previous frame and present frame. The proposed technique detects shots at first using DC(Direct Current) coefficient of DCT(Discrete Cosine Transform). The database is composed of these detected shots. Features are extracted by HMMD color model and edge histogram descriptor(EHD) among the MPEG-7 visual descriptors. And detections are performed in sequence by the proposed matching technique. Through this experiments, an improved video segmentation system is implemented that it performs more quickly and precisely than existing techniques have.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.142-148
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• 2014

A descriptor which is suitable for motion analysis by using the motion features of moving objects from the real time image sequence is proposed. To segment moving objects from the background, the background learning is performed. We extract motion trajectories of individual objects by using the sequence of the 1st order moment of moving objects. The center points of each object are managed by linked list. The descriptor includes the 1st order coordinates of moving object belong to neighbor of the pre-defined position in grid pattern, The start frame number which a moving object appeared in the scene and the end frame number which it disappeared. A video retrieval by the proposed descriptor combining global and local feature is more effective than conventional methods which adopt a single feature among global and local features.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.89-95
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• 2013

Smoking in elevators is a criminal offense that is included in a misdemeanor. Because of that smoking in elevators can be very critical for our growing children and weak women. In this paper, we would like to extract criminals doing this criminal offense to smoke in elevators. Extraction method detect difference value using modified color-X2-test and it was normalized. Next, we find frames that has occurred scene change in successive frames using the four-step algorithm of scene change detection. Finally, we present the method of smoking image retrieval and extraction in stored large amount of video. In the experiment, we show process and number of scene change detection, and the number of video searched per retrieval time. The extracted smoking video is to submit as evidence for the police or court.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1519-1530
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• 1999

오늘날 멀티미디어 정보의 양이 매우 빠른 속도로 증가함에 따라 멀티미디어 데이타베이스에 대한 효율적인 관리는 더욱 중요한 의미를 가지게 되었다. 게다가 영상과 같은 비 문자형태의 데이타에 대한 사용자들의 내용기반 검색욕구 증가로 인해 비디오 인덱싱에 대한 관심은 더욱 고조되고 있다. 따라서 본 논문에서는 우선적으로 분할된 샷 경계면에서 추출된 대표 프레임과 정지 영상 데이타베이스로부터 유사 영상과 유사 대표 프레임을 검색할 수 있는 환경을 제공한다. 우선적으로 영상에 의한 질의는 기존에 주로 사용되어온 색상 히스토그램방식을 탈피하여 본 논문에서 제안하는 CS와 GS방식을 이용하여 색상 및 방향성 정보도 고려하도록 설계하였다. 또한 얼굴에 의한 질의는 대표 프레임으로부터 얼굴 영역을 추출해 내고 얼굴의 경계선 값 및 쌍 직교 웨이블릿 변환에 의해 얻어진 2개의 특징값을 이용하여 유사 인물이 포함된 대표 프레임을 검색해 내도록 설계하였다. Abstract There is a rapid increase in the use of digital video information in recent years, it becomes more important to manage multimedia databases efficiently. There is a big concern about video indexing because users require content-based image retrieval. In this paper, we first propose query-by-image system environment which allows to retrieve similar images from the chosen representative frames or images from the image databases. This algorithm considers not only the discretized color histogram but also the proposed directional information called CS & GS method. Finally, we designe another query environment using query-by-face. In this system , user selects a people in the representative frame browser and then system extracts a face region from that frame. After that system retrieves similar representative frames using 2 features, edge information and biorthogonal wavelet transform.

• Journal of the Semiconductor & Display Technology
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• v.6 no.1 s.18
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• pp.49-52
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• 2007

The recent advances in digital imaging and computing technology have resulted in a rapid accumulation of digital media in the personal computing and entertainment industry. In addition, large collections of such data already exist in many scientific application domains such as the geographic information systems (GIS), digital library, trademark imaging, satellite imaging and medical imaging. Thus, the need for content-based retrieval from visual media, such as image and video data, is ever increasing rapidly in many applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.10-19
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• 2003

Caption information in news videos can be useful for video indexing and retrieval since it usually suggests or implies the contents of the video very well. In this paper, a new algorithm for extracting and recognizing characters from news video is proposed, without a priori knowledge such as font type, color, size of character. In the process of text region extraction, in order to improve the recognition rate for videos with complex background at low resolution, continuous frames with identical text regions are automatically detected to compose an average frame. The image of the averaged frame is projected to horizontal and vertical direction, and we apply region filling to remove backgrounds to produce the character. Then, K-means color clustering is applied to remove remaining backgrounds to produce the final text image. In the process of character recognition, simple features such as white run and zero-one transition from the center, are extracted from unknown characters. These feature are compared with the pre-composed character feature set to recognize the characters. Experimental results tested on various news videos show that the proposed method is superior in terms of caption extraction ability and character recognition rate.