Insulator Detection and Defect Classification using Rotation Invariant Local Directional Pattern
نویسندگان
چکیده
منابع مشابه
Insulator Detection and Defect Classification using Rotation Invariant Local Directional Pattern
Detecting power line insulator automatically and analyzing their defects are vital processes in maintaining power distribution systems. In this work, a rotation invariant texture pattern named rotation invariant local directional pattern (RILDP) is proposed for representing insulator image. For this at first, local directional pattern (LDP) is applied on image which can encode local texture pat...
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Article history: Available online 18 December 2013
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Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP) drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that redu...
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More and more attention has been paid to the invariant texture analysis, because the training and testing samples generally have not identical or similar orientations, or are not acquired from the same viewpoint in many practical applications, which often has negative influences on texture analysis. Local binary pattern (LBP) has been widely applied to texture classification due to its simplici...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2018
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2018.090237