Visual perception-based criminal identification: a query-based approach. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Singh, Avinash Kumar; Nandi, G. C.
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 29:Issue 1(2017)
• Page Start: 175
• Page End: 196
• Publication Date: 2017-01-02
• Subjects: Criminal identification -- dynamic query optimisation -- knowledge extraction -- knowledge representation -- classification -- reasoning -- expert system; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2015.1132266
• Languages: English
• ISSNs: 0952-813X

Abstract

Abstract: The visual perception of eyewitness plays a vital role in criminal identification scenario. It helps law enforcement authorities in searching particular criminal from their previous record. It has been reported that searching a criminal record manually requires too much time to get the accurate result. We have proposed a query-based approach which minimises the computational cost along with the reduction of search space. A symbolic database has been created to perform a stringent analysis on 150 public (Bollywood celebrities and Indian cricketers) and 90 local faces (our data-set). An expert knowledge has been captured to encapsulate every criminal's anatomical and facial attributes in the form of symbolic representation. A fast query-based searching strategy has been implemented using dynamic decision tree data structure which allows four levels of decomposition to fetch respective criminal records. Two types of case studies - viewed and forensic sketches have been considered to evaluate the strength of our proposed approach. We have derived 1200 views of the entire population by taking into consideration 80 participants as eyewitness. The system demonstrates an accuracy level of 98.6% for test case I and 97.8% for test case II. It has also been reported that experimental results reduce the search space up to 30 most relevant records.