An iris based biometric recognition system provides identification of an individual based on a unique feature or characteristic possessed by that individual. Iris recognition is consider as the most reliable and accurate biometric identification system. In this paper we explore the performance of the iris based recognition system. We take iris image of ten different people and after segmentatio...

In this paper, we are interested with the groundtruthing problem for performance evaluation of symbol recognition & spotting systems. We propose a complete framework based on user interaction scheme through a tactile device, exploiting image processing components to achieve groundtruthing of real-life documents in an semi-automatic way. It is based on a top-down matching algorithm, to make the ...

This paper presents a method of recognition of isolated offline handwritten Devanagari numerals using wavelets and neural network classifier. This method of optical character recognition takes the handwritten numeral image as input. After pre-processing, it is subjected to single level wavelet decomposition using Daubechies-4 wavelet filter. This wavelet decomposition allows viewing the input n...

Tracking human facial expression within a video image has many useful applications, such as surveillance and teleconferencing, etc. Initially, the Active Appearance Model (AAM) was proposed for facial recognition; however, it turns out that the AAM has many advantages as regards continuous facial expression recognition. We have implemented a continuous facial expression recognition system using...

In this research work, a literature review was conducted to assess the progress made in the field of image compression effects on the face recognition. The DCT algorithms were considered for the review and their application was limited only to JPEG compression. In this review, progress was made in the DCT algorithms of a single image, and a series images from a video, namely 2D DCT and 3D DCT r...

This paper describes a prototype implementation of a speech recognition system for embedded applications. The recognition system is comprised of a feature extractor and a classifier. The feature extractor is based on a 64-point Fast Fourier Transformation (FFT); the classifier is based on discrete-density Hidden Markov Models (HMM) with a variable codebook size. Training as well as classificati...

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic...

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic...

In this work we present an efficient approach for face recognition in the infrared spectrum. In the proposed approach physiological features are extracted from thermal images in order to build a unique thermal faceprint. Then, a distance transform is used to get an invariant representation for face recognition. The obtained physiological features are related to the distribution of blood vessels...

Sign Language Recognition is one of the most growing fields of research today. Many new techniques have been developed recently in these fields. Here in this paper, we have proposed a system using Eigen value weighted Euclidean distance as a classification technique for recognition of various Sign Languages of India. The system comprises of four parts: Skin Filtering, Hand Cropping, Feature Ext...