Dr. Ali Mohammed Sahan IT Dept., Technical College of Management, Middle Technical University, Baghdad, Iraq AbstractFace recognition process in human perception utilizes two kinds of features. The first are global features used to describe the whole face image, while the second are local features used to describe finer details of the face. The combined face recognition methods stimulate the te...

We have previously used Zernike moments, calculated from strokes, to recognize printed digits. We attempt to apply this system to reading digits in the White Pages.

In this paper, a new set of orthogonal moments based on the discrete classical Krawtchouk polynomials is introduced. The Krawtchouk polynomials are scaled to ensure numerical stability, thus creating a set of weighted Krawtchouk polynomials. The set of proposed Krawtchouk moments is then derived from the weighted Krawtchouk polynomials. The orthogonality of the proposed moments ensures minimal ...

moment descriptors are commonly used in applications such as image classification, pattern recognition and identification. A radial-polar representation of image coordinate space is particularly useful in the above applications, since it facilitates the derivation of rotation invariants of any arbitrary order. Zernike moments and radial-Tchebichef moments fall into the category of moments that ...

A new method is proposed for fast computation of accurate pseudo-Zernike moments for binary and gray level images. These orthogonal moments are computed as a linear combination of accurate geometric and radial geometric moments, which are computed by mathematical integration of the monomial polynomials over digital image pixels. The proposed method is fast, accurate, simple, and easy programmab...

In this paper, we present a method for automatic recognition of isolated Marathi handwritten numerals in which Zernike moments and Fourier Descriptors are used as features. After preprocessing the numeral image, Zernike moment and the Fourier Descriptor features of the numeral are extracted. These features are then fed in the k-NN classifier for classification. The proposed method is experiment...

The problem of searching a digital image in a very huge database is called Content Based Image Retrieval (CBIR). Shape is a significant cue for describing objects. In this paper, we have developed a shape feature extraction of MRI brain tumor image retrieval. We used T1 weighted image of MRI brain tumor images. There are two modules: feature extraction process and classification. First, the sha...

We present a symbol recognition method without segmentation of the document. Our approach uses Zernike moments for the coding and a multilayered Perceptron for the classifier. Recognition is independant of position and scale of symbols.