Color and Texture Based Image Retrieval Feature Descriptor using Local Mesh Maximum Edge Co-occurrence Pattern

A novel descriptor is designed and developed for extracting the features from large databases. The descriptor is known as LMeMECoP that is local mesh maximum edge co-occurrence patterns. Information of local maximum edge is collected between the possible neighbors for provided centre pixel that is the reference pixel. The maximum edge collection is in the form of mesh intended for reference pixel. The information of extracted maximum edge is utilized for forming binary bits. The co-occurrence bits are collected later for appropriate centre pixel by means of maximum edge response information. In the end, the patterns are generated from the co-occurrence bits between the provided pixels with its neighbor pixels. The combination of texture information with color information takes place for enhancing the proposed method performance. The change of RGB to HSV color space is executed for general histogram and color centered feature for each color space. Generation of final feature is executed with the integration of texture based features with color based features. The LMeMECoP assessment is executed by proposed method testing on Corel 5K with Corel 10 K and MIT VisTex dB centered on ARP (average retrieval precision). The output after investigation has shown that LMeMECoP has shown a tremendous betterment in terms of ARP on Corel-5K and Corel-10K dB.