this paper describes an enhanced facial expression recognition system. In the first step, the face localization is done using a simplified method, then the facial components are extracted and described by three feature vectors: the Zernike moments, the spectral components‘ distribution through the DCT transform and by LBP features. The different feature vectors are used separately then combined...

Nowadays Image retrieval is becomes more challenged thing in many of the fields like medical diagnosis, crime prevention, military services, architectural and engineering design, geographical information, trademark matching, etc. So there is the necessitates of effectively retrieving relevant images when needed. Thus, content-based image retrieval systems (CBIR) have become very popular for bro...

This paper introduces a new set of orthogonal moment Functions-franklin Moments (FMs). The kernel functions of FMs is Franklin set, which is a class of complete orthogonal spline function set of degree 1. The implementation of FMs does not involve any numerical approximation and has a rather low computation complexity, since the basis set has the advantages of lower order. These properties make...

This paper proposes a palmprint based verification system using low-order Zernike moments of palmprint sub-images. The Zernike moments of corresponding sub-images of live and enrolled palmprint are matched using Euclidean distance for verification. An efficient weighted fusion technique to fuse matching scores of the sub-images is proposed. The palmprint is extracted from the hand image acquire...

Traditional trademark image retrieval algorithm only using global feature easily makes mistaken retrieval, and scale invariant feature transform (SIFT) features have limited descriptive ability for image contour and high algorithm complexity. This paper proposes a trademark retrieval algorithm combining the image global features and local features. In this paper, we will firstly, extract Zernik...

In this paper we propose a new and effective image retrieval scheme using color, texture and shape features based on pseudo-Zernike moment. Image is predefined by using fast color quantization algorithm with cluster merging. A small number of dominant colors and their percentage can be obtained. The spatial features are extracted using steerable filter decomposition. This offers an efficient an...

An architecture for fast video object recognition is proposed. This architecture is based on an approximation of featureextraction function: Zernike moments and an approximation of a classification framework: Support Vector Machines (SVM). We review the principles of the moment-based method and the principles of the approximation method: dithering. We evaluate the performances of two moment-bas...

Offline Tamil Handwritten character recognition system using a combination of Zernike moments and diagonal features of Zones are proposed in this paper. The proposed recognition system yields higher rate of recognition accuracy compared to the systems developed using the conventional feature extractions using horizontal and vertical methods. Since, Zernike moments are known as better descriptor...

Handwritten automatic character recognition has attracted many researchers all over the world to contribute automatic character recognition domain. Shape identification and feature extraction is very important part of any character recognition system and success of method is highly dependent on selection of features. However feature extraction is the most important step in defining the shape of...

Super-resolution (SR) with probabilistic motion estimation is a successful algorithm to circumvent the limitation of motion estimation upon conventional superresolution methods. However, the algorithm can’t match similar patches with rotation or scale. This paper presents an efficient improved algorithm by introducing Zernike moments as representation of image invariant features into similarity...