Texture Classification Based on Gabor-like Feature
نویسندگان
چکیده
منابع مشابه
Texture Classification Based on Gabor Wavelets
This paper presents the comparison of Texture classification algorithms based on Gabor Wavelets. The focus of this paper is on feature extraction scheme for texture classification. The texture feature for an image can be classified using texture descriptors. In this paper we have used Homogeneous texture descriptor that uses Gabor Wavelets concept. For texture classification, we have used onlin...
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With the development of computer vision, robots need to detect target objects from image sequence for autonomous navigation. To identify targets, the perceptual system of autonomous robots first needs to segment the images into nonoverlapping but meaningful regions based on low-level features such as color, texture measures and shapes etc.. Being an important component, Gabor wavelets are often...
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As a regional feature, texture is a description of the spatial distribution of the image pixels. As texture can fully utilize the image information, it can become an important basis to describe and recognize the image. Compared with other image features, texture can take both the macro image properties and micro structure into consideration; therefore, feature has become a significant feature t...
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In this paper, an efficient texture classification method is proposed, which not only considers the effect of rotation, but also is scaling invariant. In our method, the Gabor wavelets are adopted to extract local features of an image, and the statistical property of the intensity values is used to represent the global feature. Then, an adaptive circular orientation normalization scheme is prop...
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The two groups of popularly used texture analysis techniques for classification problems are the statistical and signal processing methods. In this paper, we propose to use a signal processing method, the Gabor filters to produce the feature images, and a statistical method, the covariance matrix to produce a set of features which show the statistical information of frequency domain. The experi...
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ژورنال
عنوان ژورنال: The Journal of Korea Institute of Information, Electronics, and Communication Technology
سال: 2017
ISSN: 2005-081X
DOI: 10.17661/jkiiect.2017.10.2.147