• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.96-100
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• 1998

Due to expected wide spread use of DCT based image/video coding standard, it is advantageous to process data directly in the DCT domain rather than decoding the source back to the spatial domain. The block processing algorithm provides a parallel processing method since multiple input data are processed in the block filter structure. Hence a fast implementation of the algorithm is well suited. In this paper, we propose the JPEG browse by Block Transform Domain Filtering(BTDF) using subband filter banks. Instead of decompressing the entire image to retrieve at full resolution from compressed format, a user can select the level of expansion required$(2^N{\times}2^N)$. Also this approach reduces the computer cpu time by reducing the number of multiplication through BTDF in the filter banks.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.471-475
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• 2005

Recently, development of digital technology is occupying a large part of multimedia information like character, voice, image, video, etc. Research about video indexing and retrieval progresses especially in research relative to video. This paper proposes the novel notation in order to retrieve MPEG video in the international standards of moving picture encoding For realizing the retrieval-system, we detect DCT DC coefficient, and then we obtain shot to apply MVC(Mean Value Comparative) notation to image constructed DC coefficient. We choose the key frame for start-frame of a shot, and we have the codebook index generating it using feature of DC image and applying PCA(principal Component Analysis) to the key frame. Also, we realize the retrieval-system through similarity after indexing. We could reduce error detection due to distinguish shot from conventional shot detection algorithm. In the mean time, speed of indexing is faster by PCA due to perform it in the compressed domain, and it has an advantage which is to generate codebook due to use statistical features. Finally, we could realize efficient retrieval-system using MVC and PCA to shot detection and indexing which is important step of retrieval-system, and we using retrieval-system over the internet.

• 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.

• Science of Emotion and Sensibility
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• v.14 no.2
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• pp.293-300
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• 2011

The CGI(Computer-generated Image) techniques provide designers with an effective means of creating design artifacts in an automatic way. It has been pointed that two important activities while applying the CGI techniques are both image generation and managemental issues for the generated images. By applying automatic generation techniques for creation of images, designers can acquire benefits in that they can produce free style results in a simple way. Along with such benefits, it is also important for designer to identify and to establish well defined mechanisms for storing vast quantity of auto-generated CGIs. However, it is problematic to assign key-words and to classify abstract images mainly because they lack an analogy of the real world entities. This paper presents classification scheme for the abstract CGIs by applying classification and description criteria from the viewpoint of both design elements and emotional elements. Effective classification and specification can help designers build and retrieve desired images in an easy way, and make management process more simple and effective.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.20-27
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• 2003

In this paper, we implemented a content-based image retrieval system that user can choose a wanted query region of object and retrieve similar object from image database. Query image is induced to wavelet transformation after divided into hue components and gray components that hue features is extracted through color autocorrelogram and dispersion in hue components. Texture feature is extracted through autocorrelogram and GLCM in gray components also. Using features of two components, retrieval is processed to compare each similarity with database image. In here, weight value is applied to each similarity value. We make up for each defect by deriving features from two components beside one that elevations of recall and precision are verified in experiment results. Moreover, retrieval efficiency is improved by weight value. And various features of database images are indexed automatically in feature library that make possible to rapid image retrieval.

• 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 KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.724-732
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• 2001

In this paper, a new method of feature extraction of major objects to represent an image using Vector Quantization(VQ) is proposed. The principal features of the image, which are used in a content-based image retrieval system, are color, texture, shape and spatial positions of objects. The representative color and texture features are extracted from the given image using VQ(Vector Quantization) clustering algorithm with a general feature extraction method of color and texture. Since these are used for content-based image retrieval and searched by objects, it is possible to search and retrieve some desirable images regardless of the position, rotation and size of objects. The experimental results show that the representative feature extraction time is much reduced by using VQ, and the highest retrieval rate is given as the weighted values of color and texture are set to 0.5 and 0.5, respectively, and the proposed method provides up to 90% precision and recall rate for 'person'query images.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.26-36
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• 2012

Since shape of an object in an image carries important information in contents based image retrieval (CBIR), many shape description methods have been proposed to retrieve images using shape information. Among the existing shape based image retrieval methods, the method which employs invariant Zernike moment desciptor (IZMD) showed better performance compared to other methods which employ traditional Zernike moments descriptor in CBIR. In this paper, we propose a new image retrieval method which applies invariant angular radial transform descriptor (IARTD) to obtain higher performance than the method which employs IZMD in CBIR. IARTD is a rotationally invariant feature which consists of magnitudes and alligned phases of angular radial transform coefficients. To produce rotationally invariant phase coefficients, a phase correction scheme is performed while extracting the IARTD. The distance between two IARTDs is defined by combining the differences of the magnitudes and the aligned phases. Through the experiment using MPEG-7 shape dataset, the average bull's eye performance (BEP) of the proposed method is 0.5806 while the average BEPs of the exsiting methods which employ IZMD and traditional ART are 0.4234 and 0.3574, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.275-279
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• 2013

Recently, as multimedia information becomes popular, there are many studies to retrieve images based on images in the web. However, it is hard to find the matching images which users want to find because of various patterns in images. In this paper, we suggest an efficient images retrieval system based on images for finding products in internet shopping malls. We extract features for image retrieval by using SIFT (Scale Invariant Feature Transform) algorithm, repeat keypoint matching in various dimension by using PCA-SIFT, and find the image which users search for by combining them. To verify efficiency of the proposed method, we compare the performance of our approach with that of SIFT and PCA-SIFT by using images with various patterns. We verify that the proposed method shows the best distinction in the case that product labels are not included in images.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.141-152
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• 2005

A new emotion-based image retrieval method is proposed in this paper. Query emotion descriptors called query color code and query gray code are designed based on the human evaluation on 13 emotions('like', 'beautiful', 'natural', 'dynamic', 'warm', 'gay', 'cheerful', 'unstable', 'light' 'strong', 'gaudy' 'hard', 'heavy') when 30 random patterns with different color, intensity, and dot sizes are presented. For emotion image retrieval, once a query emotion is selected, associated query color code and query gray code are selected. Next, DB color code and DB gray code that capture color and, intensify and dot size are extracted in each database image and a matching process between two color codes and between two gray codes are peformed to retrieve relevant emotion images. Also, a new relevance feedback method is proposed. The method incorporates human intention in the retrieval process by dynamically updating weights of the query and DB color codes and weights of an intra query color code. For the experiments over 450 images, the number of positive images was higher than that of negative images at the initial query and increased according to the relevance feedback.