• 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.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.40-47
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• 2013

In case of wild fire, early detection of wild fire is the most important factor in minimizing the damages. In this paper, we suggest an effective system that detects wild fire using a panoramic image from a single camera with PAN/TILT head. This enables the system to detect the size and the location of the fire in the early stages. After converting RGB image input to color YCrCb image, the differential image is used to detect changes in movement of the smoke to determine the regions which may be prone to forest fire. Histogram analysis of fire flame is used to determine the possibility of fire in the predetermined regions. In addition, image matching and SURF were used to create the panoramic image. There are many advantages in this system. First of all, it is very economical because this system needs only a single camera and a monitor. Second, it shows the live image of wide view through panoramic image. Third, this system can reduce the quantity of saved data by storing panoramic images.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.703-712
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• 2003

With the explosive growth n the numbers and sizes of imaging technologies, Content-Based Image Retrieval (CBIR) has been attacked the interests of researchers in the fields of digital libraries, image processing, and database systems. In general, in the case of query-by-image, in user has to select an image from database to query, even though it is not his completely desired one. However, since query-by-sketch approach draws a query shape according to the user´s desire it can provide more high-level searching interface to the user compared to the query-b-image. As a result, query-by-sketch has been widely used. In this paper, we propose a Java-based image retrieval system that consists of sketch query and image classification. We use two features such as color histogram and Haar wavelets coefficients to search similar images. Then the Leave-One-Out method is used to classify database images. The categories of classification are photo & painting, city & nature, and sub-classification of nature image. By using the sketch query and image classification, w can offer convenient image retrieval interface to user and we can also reduce the searching time.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.168-176
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• 2014

Detecting moving objects from a video sequence is a fundamental and critical task in video surveillance, traffic monitoring and analysis, and human detection and tracking. It is very difficult to detect moving objects in a video sequence degraded by the environmental factor such as fog. In particular, the color of an object become similar to the neighbor and it reduces the saturation, thus making it very difficult to distinguish the object from the background. For such a reason, it is shown that the performance and reliability of object detection and tracking are poor in the foggy weather. In this paper, we propose a novel method to improve the performance of object detection, combining a haze removal algorithm and a local histogram-based object tracking method. For the quantitative evaluation of the proposed system, information retrieval measurements, recall and precision, are used to quantify how well the performance is improved before and after the haze removal. As a result, the visibility of the image is enhanced and the performance of objects detection is improved.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.379-387
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• 2001

We proposed an enhanced extraction method of vehicle plate, in which both the brightness variation of gray and the Hue value of HSI color model were used. For the extraction of the vehicle plate from a vehicle image, first of all, candidate regions for the vehicle plate were extracted from the image by using the property of brightness variation of the image. A real place region was determined among candidate regions by the density of pixels with the Hue value of green and white. For- extracting the feature area containing characters from the extracted vehicle plate, we used the histogram-based approach of individual characters. And we proposed and applied for the recognition of characters the enhanced ART2 algorithm which support the dynamical establishment of the vigilance threshold with the genera]iced union operator of Yager. In addition, we propose an enhanced SOSL algorithm which is integrated both enhanced ART2 and supervised learning methods. The performance evaluation was performed using 100's real vehicle images and the evaluation results demonstrated that the extraction rates of tole proposed extraction method were improved, compared with that of previous methods based un brightness variation, RGB and HSI individually . Furthermore, the recognition rates of the proposed algorithms were improved much more than that of the conventional ART2 and BP algorithms.

• The Journal of Korean Association of Computer Education
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• v.8 no.6
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• pp.103-111
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• 2005

This paper presents a novel automated threshold-decision algorithm that uses the mean and standard-deviation values obtained from the difference values of consecutive frames. At first, the calculation of difference values is obtained by the weighted ${\chi}^2$-test algorithm which was modified by joining color histogram to ${\chi}^2$-test algorithm. The weighted ${\chi}^2$-test algorithm can subdivide the difference values by imposing weights according to NTSC standard. In the first step, the proposed automatic threshold-decision algorithm calculates the mean and standard-deviation value from the total difference values, and then subtracts the mean value from the each difference values. In the next step, the same process is performed on the remained difference values, and lastly, the threshold is detected from the mean when the standard deviation has a maximum value. The proposed method is tested on various video sources and, in the experimental results, it is shown that the proposed method efficiently estimates the thresholds and reliably detects scene changes.

• Journal of Korea Multimedia Society
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• v.8 no.2
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• pp.269-278
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• 2005

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantics-based retrieval method can be available for various queries of users. In this paper, we propose a video retrieval system which support semantics retrieval of various users for massive video data by user's keywords and comparison area learning based on automatic agent. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user becomes a query image and searches the most similar key frame through color histogram comparison and comparison area learning method that proposed. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 93 percents.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.185-195
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• 2013

In this paper, we propose a video summarization technique on a smartphone, based on spatiotemporal saliency. The proposed technique detects scene changes by computing the difference of the color histogram, which is robust to camera and object motion. Then the similarity between adjacent frames, face region, and frame saliency are computed to analyze the spatiotemporal saliency in a video clip. Over-segmented hierarchical tree is created using scene changes and is updated iteratively using mergence and maintenance energies computed during the analysis procedure. In the updated hierarchical tree, segmented frames are extracted by applying a greedy algorithm on the node with high saliency when it satisfies the reduction ratio and the minimum interval requested by the user. Experimental result shows that the proposed method summaries a 2 minute-length video in about 10 seconds on a commercial smartphone. The summarization quality is superior to the commercial video editing software, Muvee.

• 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 Broadcast Engineering
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• v.22 no.3
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• pp.327-338
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• 2017

Exposure fusion is a typical image fusion technique to generate a high dynamic range image by combining two or more different exposure images. In this paper, we propose block-based exposure adjustment considering unique characteristics of human visual system and improved saturation measure to get weight map. Proposed exposure adjustment artificially corrects intensity values of each input images considering human visual system, efficiently preserving details in the result image of exposure fusion. The improved saturation measure is used to make a weight map that effectively reflects the saturation region in the input images. We show the superiority of the proposed algorithm through subjective image quality, MEF-SSIM, and execution time comparison with the conventional exposure fusion algorithm.