A Web Application-Based Secured Image Retrieval System With an IoT-Cloud Network

Abstract

Many encryption and searching techniques have been used, but they did not prove effective to support smart devices in order to provide input image. Therefore, based on these facts, an effective and novel system has been developed in this paper which is based on content-based search concentrated on encrypted images. Four type of features, namely color moment (CM), Gray level co-occurrence matrix (GLCM), hybrid of CM and GLCM, and lastly, a deep belief network (DBN) has been used here. This deep neural network is based on clustering in combination with indexing and the developed model is called as cluster-based deep belief network (CBDBN) in the present work. A web based application has also been developed using Apache Tomcat server and MATLAB engine. Analysis of many parameters like precision, recall, entropy, correlation coefficient, and time has been done here on benchmark datasets, namely WANG and COIL.

Color Image Retrieval Method Using Low Dimensional Salient Visual Feature Descriptors for IoT Applications

“…. , 8, values are given as for example (AC 1 , AC 2 , AC 3 , AC 4 , AC 5 , AC 6 , AC 7 , AC 8 ) � (1, 1, 1, 1, 0, 1, 1, 0) � 246 which is the decimal representation and this decimal value is represented by array AC df i . Tus, the collected values of an image is given as…”

“…The retrieval of the desired images from a digital repository with semantically varied categories is a very tedious task for many researchers, especially in cloud assisted IoT [ 7 ]. The image retrieval is a searching technique in several real-world applications, such as medical imaging [ 8 ], searching individual video frames [ 9 ], object retrieval [ 10 ], image classification [ 11 ], digital libraries [ 12 ], and multimedia event detection [ 13 ].…”