Person identification using vascular and non-vascular retinal features. (July 2016)

• Record Type: Journal Article
• Authors: Waheed, Zahra; Usman Akram, M.; Waheed, Amna; Khan, Muazzam A.; Shaukat, Arslan; Ishaq, Mazhar
• Is Part Of: Computers & electrical engineering. Volume 53(2016)
• Page Start: 359
• Page End: 371
• Publication Date: 2016-07
• Subjects: Biometric system -- Retina recognition -- Vascular-based retinal recognition -- Non-vascular-based retinal recognition; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.03.010
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Novel methods for personal identification using retinal images. Vascular based method involves the use of vessel properties of retinal images with improved vessel segmentation algorithm by catering pathological lesions. Non-vascular based method uses novel structural features structure to perform person identification. Graphical abstract: Abstract: Retina recognition is the most stable and reliable biometric system due to its stability, uniqueness and non-replicable nature of vascular pattern. On the other hand, the complexity of vascular pattern in diseased retina makes the extraction of blood vessels very hard, which majorally effects the recognition rate. The main aim of this paper is to design a robust retinal recognition system with reduced computational complexity and to explore novel retinal features. This paper presents two different approaches for retinal recognition; one is vascular-based feature extraction with an improved vessel segmentation algorithm and second is non-vascular based feature extraction. Vascular-based method uses vessel properties of retinal images and aims to improve the efficiency of retinal recognition system. Whereas, non-vascular based method intends to analyze non-vessel properties of retinal images in order to reduce time complexity. The proposed system is assessed on two local and three public databases.