Comprehensive review of continuous and discrete orthogonal moments in biometrics

ABSTRACT

Orthogonal moments (OM) are extensively used for image enhancement, representation and comparison. They are basically derived through mutually perpendicular polynomials which may be continuous and discrete. Primary continuous OM include Zernike, Pseudo-Zernike, Legendre and Bessel–Fourier moments and the prominent discrete OM are Krawtchouk and Tchebichef moments. These moments involve minimum information redundancy and therefore can be applied to various fields like face recognition, edge detection, palm print verification and content-based retrieval. This paper presents the comparative review of the moments in the fields of face, palm print and iris recognition. OM yield better results than non-orthogonal moments because they are robust to noise as well as rotation, scaling and transformation invariant. This paper summarizes the work done by various authors in biometrics for both continuous and discrete moments.

KEYWORDS:

• Orthogonal moments
• biometrics
• fractional orthogonal moments
• image representation

Disclosure statement

No potential conflict of interest was reported by the authors.