Content Based Image Retrieval Using Support Vector Machine (SVM)

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Details

Content Based Image Retrieval (CBIR) is a developing trend in Digital Image Processing for searching and retrieving the query image from wide range of databases. Conventional content-based image retrieval (CBIR) schemes have following limitations: 1. It is slow 2. difficult to label negative examples; 3. Accuracy is poor in a single step; we propose a new two- step strategy in which first step is feature extraction using low level features (colour, shape and texture) while SVM classifier is used in the second step to handle the noisy positive examples. Thus, an efficient image retrieval algorithm based on color-correlogram for color feature extraction, wavelet transformation for extracting shape features and Gabor wavelet for texture feature extraction.

Autorentext

O Dr. Aniruddha Shelotkar trabalha como Chefe do Departamento de Engenharia Electrónica e de Telecomunicações na Faculdade de Engenharia e Tecnologia de Jagadambha, Yavatmal, Maharashtra

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786200094056
    • Genre Elektrotechnik
    • Sprache Englisch
    • Anzahl Seiten 68
    • Größe H220mm x B150mm x T5mm
    • Jahr 2019
    • EAN 9786200094056
    • Format Kartonierter Einband
    • ISBN 6200094055
    • Veröffentlichung 24.09.2019
    • Titel Content Based Image Retrieval Using Support Vector Machine (SVM)
    • Autor Aniruddha Shelotkar , Dattakrushna Metange
    • Gewicht 119g
    • Herausgeber LAP LAMBERT Academic Publishing

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