Cloud based CBIR SaaS Model using Hybrid Wavelet Type I Type II based Texture Feature Extraction
Content Based Image Retrieval (CBIR) is a technique used for efficient retrieval of relevant images from large databases based on features extracted from the image. Image Feature extraction is a method used to extract feature vectors of an image based on color, shape, texture etc. This paper proposes a system that can be used for retrieving images related to query image. Kekre's Hybrid Wavelet Type I Type II are used for feature extraction. Hybrid Wavelet transforms are generated using orthogonal transforms such as Discrete Cosine transform (DCT) Walsh transform, Haar transform, Hartley transform, Kekre transform in any combination. The feature vectors of the database images are stored and then are compared to the feature vectors of the query image. The image information is sorted in decreasing order of similarity. This paper aims at implementing a CBIR system on cloud due to which services of CBIR will be dynamically made available resulting in increase in applications processing speed, scalability, flexibility and availability. Similarity measures like precision and recall are used for performance evaluation.