TITLE:
Palm Print Identification Using Improved Histogram of Oriented Lines
AUTHORS:
M. Arunkumar, S. Valarmathy
KEYWORDS:
Histogram of Oriented Gradients, Histogram of Oriented Lines, Improved Histogram of Oriented Lines, Principal Component Analysis
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.8,
June
16,
2016
ABSTRACT: Automatic palmprint
identification has received much attention in security applications and law
enforcement. The performance of a palmprint identification system is improved
by means of feature extraction and classification. Feature extraction methods
such as Subspace learning are highly sensitive to the rotation variances,
translation and illumination in image identification. Thus, Histogram of
Oriented Lines (HOL) has not obtained promising performance for palmprint
recognition so far. In this paper, we propose a new descriptor of palmprint
named Improved Histogram of Oriented Lines (IHOL), which is an alternative of
HOL. Improved HOL is not very sensitive to changes of translation and
illumination, and has the robustness against small transformations whereas the
small translation and rotations make no change in histogram value adjustment of
the proposed work. The experiment results show that based on IHOL, with
Principal Component Analysis (PCA) subspace learning can achieve high recognition
rates. The proposed method (IHOL-Cosine distance) improves 1.30% on PolyU I
database, and similarly (IHOL-Euclidean distance) improves 2.36% on COEP
database compared with existing HOL method.