Extraction of Texture Information from Fuzzy Run Length Matrix
نویسندگان
چکیده
منابع مشابه
Extraction of Texture Information from Fuzzy Run Length Matrix
For a precise texture classification and analysis, a run length matrix is constructed on the Local Binary pattern using fuzzy principles in the present paper. The proposed Run Length Matrix on Fuzzy LBP (RLM-FLBP) overcomes the disadvantages of the previous run length methods of texture classification that exist in the literature. LBP is a widely used tool for texture classification based on lo...
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We use a multilevel dominant eigenvector estimation algorithm to develop a new run-length texture feature extraction algorithm that preserves much of the texture information in run-length matrices and significantly improves image classification accuracy over traditional run-length techniques. The advantage of this approach is demonstrated experimentally by the classification of two texture data...
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With the dramatic increase of 3D imaging techniques, there is a great demand for new approaches in texture analysis of volumetric data. In this paper, we present a new approach for volumetric texture analysis using a runlength encoding matrix and its texture descriptors. We experiment with our approach on the volumetric data generated from two normal Computed Tomography (CT) studies of the ches...
متن کاملTexture Analysis and Classification Based on Fuzzy Triangular Greylevel Pattern and Run- Length Features
Your Texture analysis is one of the most important techniques used in the analysis and interpretation of images, consisting of repetition or quasi repetition of some fundamental image elements. The present paper derived Fuzzy Triangular Greylevel Pattern (FTGP) to overcome the disadvantages of LBP and other local approaches. The FTGP is a 2 x 2 matrix that is derived from a 3 x 3 neighborhood m...
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sever& texture features are introduced from a proposed higher-order statistical matrix, the gray level gap length matrix (GLGLM). The GLGLM measures the gray level variations in an image. It complements the gray level run length matrix (GLRLM) and is more superior when the number of gray level is large. Features extracted from the weighted GLGLM can be used to estimate the size distribution of ...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2012
ISSN: 0975-8887
DOI: 10.5120/8722-2594