Visual Recognition Using Directional Distribution Distance

Automatic Face Recognition via Local Directional Patterns

Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...

Using Directional Distance Functions to Determine Ranking Ranges in Cross-efficiency Evaluations

Local Derivative Pattern with Smart Thresholding: Local Composition Derivative Pattern for Palmprint Matching

Palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. Texture is one of the most important features extracted from low resolution images. In this paper, a new local descriptor, Local Composition Derivative Pattern (LCDP) is proposed to extract smartly stronger...

Holistic Farsi handwritten word recognition using gradient features

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...

Measurement of prot inefficiency in presence of interval data using the directional distance function

In many applied programs in real-life problems, both physical inputs and outputsare heterogeneous which in this case the ecient cost and income modelcan not apply to evaluate the cost and income of related turnover. So, a measurementbased on the directional value of prot was presented which we havedeveloped it in this paper and have computed it for interval data. In fact, wehave measured the in...