A novel methodology for gender classification is presented in this paper. It extracts feature from local region of a face using gray color intensity difference. The facial area is divided into sub-regions and GDP histogram extracted from those regions are concatenated into a single vector to represent the face. The classification accuracy obtained by using support vector machine has outperforme...

Content Based Image Retrieval is a technique which uses visual contents for searching images from large scale image databases Information extracted from images such as color, texture and shape are known as feature vectors. Using multiple feature vectors to describe an image during retrieval process increases the accuracy when compared to the retrieval using single feature vector. The objective ...

In recent years, Lowe’s Scale Invariant Feature Transform (SIFT) algorithm has become a widely used tool for object recognition. One shortcoming is that it only works on grayscale image intensities. In this paper, we propose extending the SIFT descriptor to also incorporate color information in a novel fashion. The keypoint descriptor proposed in this paper is a superset of the original feature...

In this paper we address the issue of recognizing Farsi handwritten words. Two types of gradient features are extracted from a sliding vertical stripe which sweeps across a word image. These are directional and intensity gradient features. The feature vector extracted from each stripe is then coded using the Self Organizing Map (SOM). In this method each word is modeled using the discrete Hidde...

This paper presents the integration of color histogram and DBC co-occurrence matrix for content based image retrieval. The exit DBC collect the directional edges which are calculated by applying the first-order derivatives in 0o, 45o, 90o and 135o directions. The feature vector length of DBC for a particular direction is 512 which are more for image retrieval. To avoid this problem, we collect ...

background : labeling, gathering mutual information, clustering and classification of central nervous system tumors may assist in predicting not only distinct diagnoses based on tumor-specific features but also prognosis. this study evaluates the epidemi- ological features of central nervous system tumors in children who referred to mahak’s pediatric cancer treatment and research center in tehr...