Hand geometry based user identification using minimal edge connected hand image graph

Abstract

In a previously reported work, the user's hand is represented as a weighted undirected complete connected graph and spectral properties of the graph are extracted and used as feature vectors. To reduce the complexity in representing the hand image as a complete connected graph and to achieve the higher identification rate, the hand image is sought to be represented as minimal edge connected graph. The experiments are conducted separately for 16 topologies of minimal edge connected graph selected empirically to investigate the performance of the hand-geometry system. The prominent edges of hand image graph are identified experimentally by computing the identification rate. In this study, an innovative peg-free handgeometry-based user identification system using spectral properties of a minimal edge connected graph representation of hand image is proposed. The multiclass support vector machine is employed for identification of the claimed user. The geometrical information embedded in the prominent edges will contribute to achieve better identification rate. The experimentation is carried on two databases, namely GPDS150 hand database and hand images of VTU-BEC-DB multimodal database. The minimal edge connected graph with 30 prominent edges of hand image graph achieves better identification with a faster rate.

Comparative Study of Computational Intelligence Paradigms for Intelligent Access Control Based on Biometrics Methodologies

“…However, they affected even from tiny back-ground changes which cannot be sidestepped. A small amount of storage space is required to save the hand geometry model as contrasted to the palm-print (Angadi and Hatture, 2018). While the condition of the skin (i.e., dirt, dirt, scars, etc.)…”

Hand geometry recognition: an approach for closed and separated fingers

“…Traditional methods of identification which include password, cards, tokens and so on are prone to being forgotten and easily getting lost [1], [2]. Biometrics is the use of a person's behavioral or physiological trait for identification [3], [4]. Biometrics can be classified as being physiological or behavioral.…”

“…Hand geometry is the use of measurements taken from the human hand for recognition [6]. It is a physiological trait and several researchers have examined this biometric trait for identification [4], [7], [8]. Some of the advantages of this biometrics include easy of capture, easy integration with other biometric traits such as palmprint [9].…”

“…However, challenges to the use of this biometrics include restriction of hand pose during capture [8]. In most literatures, the approach is to specify that users are to keep their fingers separate during capture [1], [4], [7]. In some systems however, users are advised to keep their hands together during capturing [10], [11].…”

“…A user identification system that made use of wavelet feature of human geometry graph was presented by [4]. The system made use of GPDS150 hand database.…”