Open AccessMulti-directional Feature Positioning Retrieval Method of Random Encrypted Images
Author(s) -
Fuwei Huang
Publication year - 2021
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
ISSN - 1998-4464
DOI - 10.46300/9106.2021.15.96
Subject(s) - artificial intelligence , encryption , computer vision , feature (linguistics) , computer science , feature detection (computer vision) , binary image , image (mathematics) , pattern recognition (psychology) , image retrieval , image processing , philosophy , linguistics , operating system
Image encryption is an effective means to ensure image information security, but image encryption makes image features hidden, resulting in blurred image positioning features and cannot provide queryable rules. In this paper, the multi-direction feature retrieval method of random encrypted images is studied comprehensively. Multidirectional binary wavelet is used to decompose specific images, and multi-resolution analysis is used to extract multi-direction features of specific images. The method of image location optimization in random encrypted images is used to eliminate the excessive and repeated image features contained in the specific image by image verification, and the probability of image location errors is reduced. The specific image is retrieved by identifying frequent item sets in random encrypted images that are identical to the multidirectional features of a particular image. The results show that the method can locate the random encrypted image effectively. The accuracy of the image location and the average accuracy of the feature points are about 95 % and 97.3 % respectively, and the anti-noise ability is strong. It provides a scientific means for the rapid positioning of efficient images.