Browsing by Author "Shih, JL"

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A context-based approach for color image retrieval
(2002-03-01)
Shih, JL
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Chen, LH
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資訊工程學系
;
Department of Computer Science
In this paper, a color image retrieval method based on the primitives of images will be proposed. First, the context of each pixel in an image will be defined. Then, the contexts in the image are clustered into several classes based on the algorithm of fast noniterative clustering. The mean of the context in the same class is considered as a primitive of the image. The primitives are used as feature vectors. Since the numbers of primitives between images are different, a specially designed similarity measure is then proposed to do color image retrieval. To better adapt to the preferences of users, a relevance feedback algorithm is provided to automatically determine the weight of each primitive according to the user's response. To demonstrate the effectiveness of the proposed system, several test databases from Corel axe used to compare the performances of the proposed system with other methods. The experimental results show that the proposed system is superior to others.
A new system for trademark segmentation and retrieval
(2001-11-01)
Shih, JL
;
Chen, LH
;
資訊工程學系
;
Department of Computer Science
With the increase in the number of trademarks, trademark imitation has become a serious problem. Thus, building an efficient trademark retrieval system is imperative. In this paper, such a system is presented. First, a semi-automatic segmentation method is proposed to extract the shapes of those representative objects, called 'masks', in each trademark. Next, some features are selected to describe a mask. These include invariant moments, the histogram of edge directions, and two kinds of transform coefficients that are robust to geometric deformation. Then, based on the rank of the feature distance, a similarity measure is provided to do the similar trademark retrieval. Finally, a feedback algorithm is also proposed to automatically determine the weight of each feature according to the user's response. Furthermore, in order to show the effectiveness of the proposed system, two databases from MPEG-7 test database are used to compare the performances of the proposed system and those methods using chain code, Zernike moments or MPLV as features. The experimental results show that the proposed system is superior to others. (C) 2001 Elsevier Science B.V. All rights reserved.
Colour image retrieval based on primitives of colour moments
(2002-12-01)
Shih, JL
;
Chen, LH
;
資訊工程學系
;
Department of Computer Science
A colour image retrieval method based on the primitives of colour moments is proposed. First, an image is divided into several blocks. Then, the colour moments of all blocks are extracted and clustered into several classes. The mean moments of each class are considered as a primitive of the image. All primitives are used as features. Since two different images may have different numbers of features, a new similarity measure is then proposed. To demonstrate the effectiveness of the proposed method, two test databases from Corel are used to compare the performances of the proposed method with other existing ones. The experimental results show that the proposed method is usually better than the others. Furthermore, since for a few special types of images, other methods may have better results occasionally, a relevance feedback algorithm is also provided to automatically determine the best method according to the user's response.