Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Materials science & Computer science. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

An Approach for Image Enhancement Using Fuzzy Inference System for Noisy Image

Abstract: Image enhancement is a technique to improve the quality of an image. The aim of image enhancement technique is to improve the interpretability or perception of information in images for human viewers, or to provide better input for other automated image processing techniques. This paper presents a fuzzy grayscale enhancement technique for low contrast image corrupted by Gaussian noise. The degradation of the low contrast image is mainly caused by the inadequate lighting during image capturing and thus eventually resulted in non uniform illumination in the image. The proposed method has better performance than available methods in the enhancement of noisy images and has been validated by the performance measures like PSNR,SNR,RMSE,MSE.

An Unconstrained and Effective Approach of Script Identification for Online Bilingual Handwritten Text

Abstract: A number of monolingual online handwriting recognition (OHR) systems were proposed by researchers for languages like English, Chinese, Japanese, Hindi, Punjabi, Tamil, Bangla, Arabic and many more. But very few researchers have worked on bilingual or multilingual OHR systems, as the challenging part of these systems is the identification of scripts during recognition of intermixed words. In this paper, a bilingual OHR system is proposed for the mixed text containing words, written by using two scripts Gurmukhi (for Punjabi language) and Roman (for English language). For converting handwritten intermixed text to digital text, two steps have been implemented: first, to identify the script of segmented handwritten word and second, to run the respective script recognition engine. Multilayered perceptron neural network classifier along with directional code feature has been implemented to identify the script of segmented handwritten word. Considerable results have been observed for the script identification process.