A User Oriented Image Retrieval Using Feature Extracted By Dot diffusion Block Truncation Coding
Admile Nandkumar Sushen, A.B Kanase, Radhika Khiste · 2019
In the field of Image Processing image Retrieval is an key research area. In many applications such as logo identification, crime investigation it necessary to identify or search the particular image. For that purpose image retrieval is mostly used. To retrieve the more similar image from the large image dataset number of techniques are available, out of which DDBTC is used in this papaer. Four number of image features are derived using DDBTC. Image features are obtained using color quantizers and Bitmap image. The first two features such as Color Co-occurrence Features (CCF) and Color Histogram Features (CHF) are obtained using color quantizers but other two features such as Bit Pattern Feature (BPF) and Bit Histogram Feature (BHF) are derived from Bitmap image. The five different distance metrics are used to measure the similarity between two images. The simulated results shows proposed Technique can shows the better result in the form of Average Precision rate (APR) and Average Recall Rate (ARR) as compared to other techniques.