Face Encryption based on Feature Extraction Supported by Canny Edge Detector

Autor: Abeer Salim Jamil, Nidaa Flaih Hassan, Raghad Abdulaali Azeez
Rok vydání: 2022
Předmět:
Zdroj: Webology. 19:1716-1730
ISSN: 1735-188X
DOI: 10.14704/web/v19i1/web19115
Popis: Individual privacy protection is regarding a subject in surveillance and security areas. Protection of people's faces in image in linking with complex info, abused cases, involvement, and others on public broadcasting media and social networks are very important. Partial encryption human face is selected to reduce the computational requirements for huge volumes of image data and reducing the computational processing time required to conduct the entire image. In this paper, a new fast algorithm is proposed to encrypt partially human face, at first human face is detected using vole and jones algorithm, features points are extracted from face region to be encrypted, these features points are determined by using Canny edge detector since Canny edge algorithm considers the best edge detector with decent localization properties marked edges areas similar to the edges in the actual image as possible, i.e. that it is an essential feature. Furthermore, the importance of the key for the encryption process and its significant role in increasing and improving security, a new method for generating key is proposed making them resistant to attackers. The suggested encryption algorithms produced good results in the encryption process, since it has a shorter encrypting period and a greater encrypting effect, according to experimental results.
Databáze: OpenAIRE