Volume 7 Issue 1 - May 2016

  • 1. Comparative study of image retrieval using shape as prominent feature

    Authors : Anita Kinnikar, Padmashree Desai

    Pages : 690-694

    DOI : http://dx.doi.org/10.21172/1.71.098

    Keywords : CBIR, feature vector, similarity measures, wavelet decomposition, local binary patterns.

    Abstract :

    The process of retrieving relevant images from an expansive accumulation is broadly utilized as a part of uses of computer vision. So as to enhance the retrieval effectiveness, a efficient and accurate framework is required. Retrieving the similar images with the help of image features such as shape, color and texture is referred as content based image retrieval (CBIR). It is extracted and represented in the form of feature vector. The images have the minimum distance between their feature vectors, if they are most similar. This paper provides the correlation of various CBIR frameworks and similarity measures are used to find the similarity between two images. We are proposing new framework for image retrieval using wavelet decomposition and Local Binary Patterns (LBP) using shape as prominent feature by identifying issues in existing CBIR systems.

    Citing this Journal Article :

    Anita Kinnikar, Padmashree Desai, "Comparative study of image retrieval using shape as prominent feature ", Volume 7 Issue 1 - May 2016, 690-694