2014Unpublished venueRequires access

Analysis of Geometric, Zernike and United Moment Invariants Techniques Based on Intra-class Evaluation

Mohd Wafi Nasrudin, Shahrul Nizam Yaakob, Rozmie Razif Othman, Iszaidy Ismail, M. I. Jais, Aimi Salihah Abdul Nasir

Open publisher page 5 citations

Abstract

In this paper, three moment invariants techniques have been used to extract the shape properties of the image. There are geometric moment, zernike moment and united moment invariants. These moment invariants have been used to analyze the image due to its invariant features of an image based on scaling factor and rotation. A set of equations known as intra-class analysis has been applied to measure the similarity of feature vector that represent the same object. The results obtained in this study have been analyzed and compared in terms of intra-class analysis in order to find the best technique among the three different types of moments. Based on the results that have been obtained by using the similar image, it is found that the geometric and united moment invariants techniques are better with small values of total percentage mean absolute error (TPMAE) as compared to zernike moment invariants.

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What this paper is about

In this paper, three moment invariants techniques have been used to extract the shape properties of the image. There are geometric moment, zernike moment and united moment invariants. These moment invariants have been used to analyze the image due to its invariant features of an image based on scaling factor and rotation. A set of equations known as intra-class analysis has been applied to measure the similarity of feature vector that represent the same object. The results obtained in this study have been analyzed and compared in terms of intra-class analysis in order to find the best technique among the three different types of moments. Based on the results that have been obtained by using the similar image, it is found that the geometric and united moment invariants techniques are better with small values of total percentage mean absolute error (TPMAE) as compared to zernike moment invariants.

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Available abstract

In this paper, three moment invariants techniques have been used to extract the shape properties of the image. There are geometric moment, zernike moment and united moment invariants. These moment invariants have been used to analyze the image due to its invariant features of an image based on scaling factor and rotation. A set of equations known as intra-class analysis has been applied to measure the similarity of feature vector that represent the same object. The results obtained in this study have been analyzed and compared in terms of intra-class analysis in order to find the best technique among the three different types of moments. Based on the results that have been obtained by using the similar image, it is found that the geometric and united moment invariants techniques are better with small values of total percentage mean absolute error (TPMAE) as compared to zernike moment invariants.

Key concepts: Zernike polynomials, Moment (physics), Image moment, Velocity Moments, Mathematics, Invariant (physics), Scaling, Pattern recognition (psychology)

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