GDL

Efficient CBIR Using Color Histogram Processing

ISSN : 0976 - 710X
Journal from gdlhub / 2017-08-14 11:52:33
Oleh : Neetu Sharma. S1,Paresh Rawat . S1 and Jaikaran Singh.S2, 1Truba Institute of Engineering and Information Technology, Signal & Image Processing : An International Journal
Dibuat : 2012-06-26, dengan 1 file

Keyword : CBIR, Image Retrieval, Feature extraction, Global descriptor.
Subjek : Efficient CBIR Using Color Histogram Processing
Url : http://airccse.org/journal/sipij/papers/2111sipij08.pdf
Sumber pengambilan dokumen : Internet

The need for efficient content-based image retrieval system has increased hugely. Efficient and effective


retrieval techniques of images are desired because of the explosive growth of digital images. content based


image retrieval (CBIR) is a promising approach because of its automatic indexing retrieval based on their


semantic features and visual appearance. The similarity of images depends on the feature


representation.However users have difficulties in representing their information needs in queries to content


based image retrieval systems. In this paper we investigate two methods for describing the contents of


images. The first one characterizes images by global descriptor attributes, while the second is based on


color histogram approach.To compute feature vectors for Global descriptor, required time is much less as


compared to color histogram. Hence cross correlation value & image descriptor attributes are calculated


prior histogram implementation to make CBIR system more efficient.The performance of this approach is


measured and results are shown. The aim of this paper is to compare various global descriptor attributes


and to make CBIR system more efficient. It is found that further modifications are needed to produce better


performance in searching images.

Deskripsi Alternatif :

The need for efficient content-based image retrieval system has increased hugely. Efficient and effective


retrieval techniques of images are desired because of the explosive growth of digital images. content based


image retrieval (CBIR) is a promising approach because of its automatic indexing retrieval based on their


semantic features and visual appearance. The similarity of images depends on the feature


representation.However users have difficulties in representing their information needs in queries to content


based image retrieval systems. In this paper we investigate two methods for describing the contents of


images. The first one characterizes images by global descriptor attributes, while the second is based on


color histogram approach.To compute feature vectors for Global descriptor, required time is much less as


compared to color histogram. Hence cross correlation value & image descriptor attributes are calculated


prior histogram implementation to make CBIR system more efficient.The performance of this approach is


measured and results are shown. The aim of this paper is to compare various global descriptor attributes


and to make CBIR system more efficient. It is found that further modifications are needed to produce better


performance in searching images.

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