Content Based Image Retrieval Using Color Mean with Feature Classification Using Naïve Bayes

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Navdeep Kaur
Rajbhupinder Kaur

Abstract

With the evolution of the Internet, and the
availability of image capturing devices such as advanced
cameras, picture scanners, the size of advanced image
accumulation is expanding quickly. Efficient image
searching, browsing and retrieval devices are required by
clients from different domains, including remote sensing,
fashion, wrongdoing prevention, publishing, medicine,
architecture, etc. Here we are extracting color mean features
and color standard deviation feature with the proposed
method consists of HMMD (Hue Min Max Difference) color
plane. It is proved in research work that HMMD along with
color mean features and color standard deviation feature is
tend to reduced the size of feature vectors, storage space and
gives high performance than, RGB-color mean feature.
Further, HMMD color space model will be used to improve
the feature extraction and improve the precision. At the end,
results are presented to show the efficiency of the proposed
method.


Keywords: HMMD, CBIR, Feature Extraction, Precision,
Recall.

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