Retrieval Architecture with Classified Query for Content Based Image Recognition

Abstract

The consumer behavior has been observed to be largely influenced by image data with increasing familiarity of smart phones and World Wide Web. Traditional technique of browsing through product varieties in the Internet with text keywords has been gradually replaced by the easy accessible image data. The importance of image data has portrayed a steady growth in application orientation for business domain with the advent of different image capturing devices and social media. The paper has described a methodology of feature extraction by image binarization technique for enhancing identification and retrieval of information using content based image recognition. The proposed algorithm was tested on two public datasets, namely, Wang dataset and Oliva and Torralba (OT-Scene) dataset with 3688 images on the whole. It has outclassed the state-of-the-art techniques in performance measure and has shown statistical significance.

Feature Extraction and Content Based Image Retrieval for High Resolution Remote Sensing Images

“…Das et al [9] proposed an approach where extracting the features of an image is achieved through image binarization. This enhances retrieval of images and its identification using content based image recognition.…”

An efficient similarity measure for content based image retrieval using memetic algorithm

“…Das et al [8] described a method for extraction of features through binarization of images to enhance images retrieval and identification using content based image recognition. The authors tested their system using two public datasets with a sum of 3688 images.…”

Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

“…Among existing ANN techniques, hashing approaches are proposed to map images to compact binary codes that approximately preserve the data structure in the original space [2][3][4][5][6]. Due to the high query speed and low memory cost, the hashing and image binarization techniques have become the most popular and effective techniques to enhance identification and retrieval of information using contentbased image recognition [4,[7][8][9][10][11][12][13][14][15][16]. Instead of real-valued features, images are represented by binary codes so that the time and memory costs of search can be greatly reduced [17].…”