Affiliations: [a] MIT, Academy of Engineering, Alandi, Pune, India
| [b] Symbiosis Institute of Technology Lavle, Pune, MH, India
| [c] Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India
| [d] Founder DHI Training and Research Consultancy, Pune, MH, India
| [e] G H Raisoni College of Engineering and Management, Wagholi, Pune
| [f] Sinhgad Academy of Engineering Kondhwa, Pune, MH, India
Correspondence:
[*]
Corresponding author. Sandeep Dwarkanath Pande, Department of Computer Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, MH, India. E-mail: sandeepdwarkanathp@gmail.com.
Abstract: Due to the evolution in the digital domain limitless multimedia is generated daily. It creates a necessity of potential and appealing image resuscitation system. In this paper, a shape and texture-based image retrieval system is proposed that estimates the resemblances of each query image with the images stored in the repository in the form of shape and textural facets and retrieves the images within an expected range of resemblance. The proposed approach employs a statistical approach for image retrieval. The proposed approach takes into account discriminative features of the input image for generating the shape and texture descriptors that produce outstanding results for image databases of restricted variety, which merely includes homogeneous patterns, this approach yielded satisfactory results. For texture images it uses the spatial gray level dependency matrix (SGLDM) and proposes an algorithm to compute the the inverse difference moment (IDM) as the optimal image representative feature. It further employs K-Nearest Neighbour (KNN) classifier for the classification and retrieval tasks. The proposed system outperforms the various other ultra-modern content-based image retrieval (CBIR) systems in many respects.
