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The research of texture similarity is very important component of content-based image retrieval system. Firstly the rotation invariance of gray-primitive co-occurrence matrix was proved in this paper, then a new texture image retrieval technique based on gray-primitive co-occurrence matrix was presented. The result of experiment indicates that the algorithm proposed has low computational complexity...
We present a novel DCT technique for digital watermarking of textured images based on the concept of gray-level co-occurrence matrix (GLCM). We provide analysis to describe the behavior of the method in terms of correlation as a function of the offset for textured images. We compare our approach with another spatial and temporal domain watermarking techniques and demonstrate the potential for robust...
We propose a novel statistical approach for color texture modeling and classification based on cooccurrence matrices and discrete finite mixture models. Our statistical model assigns relevance weights to discrete cooccurrence features that are considered as random variables. Experimental results are presented to illustrate the merits of our approach on a difficult problem which is the categorization...
Since the texture is an important feature of smoke, a novel method of texture analysis is proposed for real-time fire smoke detection. The texture analysis is based on gray level co-occurrence matrices (GLCM) and can distinguish smoke features from other none fire disturbances. For the realization of real-time fire detection, block processing technique is adopted and the computation of texture features...
In order to improve the average recall rate and the average precision rate of image retrieval, an improved fusion algorithm of the weighted features is presented. Firstly,the shape features of images are extracted by using the moment invariant method based on 7 central moments. Meanwhile,the texture features of images are calculated by using the Gray-level Co-occurrence matrix. Then the elements of...
In this paper, we propose an effective method based on fractal dimension calculation by the area cover for extraction of shift invariant multiwavelet features of texture images. The feature extraction process involves a normalization followed by a shift invariant multiwavelet packet transform. The normalization converts a given image into a size invariant image which is then passed to the shift invariant...
In this article a construction of hybrid colour space from a set of classic colours spaces by using the algorithm MRMR is proposed. This algorithm is based on the mutual information. Our approach is evaluated on SPOT HRV (XS) image representing two forest areas in the region of Rabat. Feature extraction is done by the cooccurrence matrix. The SVM (Support Vectors Machine) classifier is used.
In this paper, we investigate both linear and circular stochastic models in the context of texture discrimination. These models aim at representing the magnitudes and orientations obtained by a complex wavelet decomposition, such as the steerable pyramid.The novelty consists in considering specific parametric models for circular data such as von Mises and psi- distributions to describe the distributions...
To achieve efficient image retrieval, this paper applied the five texture edge directions, including 0deg, 45deg, 90deg, 135degand nondirection, recommended by MPEG-7 standards to generalized co-occurrence matrix method. The new method firstly constructs five generalized co-occurrence matrices by computing the neighboring average of pixels in a fixed window in five directions respectively. And then...
The content-based image retrieval (CBIR) is a hot topic recently. In this paper, a novel algorithm, namely a watershed-based texture image retrieval algorithm, is proposed. The algorithm mainly consists of three parts. Firstly, after reduced the noise by the open-closing by reconstruction, the image is segmented into regions by an improved watershed transformation. Secondly, the segmentation regions...
This paper proposes a texture-based method to spoof-proof a fingerprint biometric system. The fundamental basis of this anti-spoofing method is that, real fingerprint exhibits different textural characteristics from a spoof one. Textural measures based on wavelet energy signatures and gray level co-occurrence matrix (GLCM) features are used to characterize fingerprint texture. Dimensionalities of...
Wavelet transform provides several important characteristics which can be used in a texture analysis and classification. In this work, an efficient texture classification method, which combines concepts from wavelet and co-occurrence matrices, is presented. An Euclidian distance classifier is used to evaluate the various methods of classification. A comparative study is essential to determine the...
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