The DCR application for Degraded Character Recognition was developed for the DEA (Diplôme d’Études Approfondies)’s thesis. The main objective is to recognize characters, degraded by an acquisition from a lowresolution camera. Several steps are needed and are detailed in this thesis from the thresholding step, which converts a gray-level picture in a black and white one, to the post-correction s...

Touchpad based devices like phones and tablets are now ubiquitous and growing even more in popularity. Due to their form factors, however, otherwise standard means of input like keyboards are less effective in these devices. Infact using scribbling to recognize handwriting is a viable alternative. In this project we investigated a method of recognizing handwritten characters to allow automatic ...

Although optical character recognition of printed texts has been a focus of research for the last few decades, Arabic printed text, being cursive, still poses a challenge. The challenge is twofold: segmenting words into letters and identifying individual letters. We describe a method that combines the two tasks, using multiple grids of SIFT descriptors as features. To construct a classifier, we...

License plate character recognition is an integral part in Intelligent Transportation Systems. Traditional methods used for number plate recognition were OCR, Optical Character Recognition and Formula Based Recognition. As Neural Network is an intelligence engine, it ensures greater accuracy rate along with better recognition speed. In this system, recognition is done with the help of Neural Ne...

Optical character recognition refers to the process of translating segmented hand-written images or typewritten images into machine editable text. In this study, we propose a Tamil palm leaf manuscripts character recognition system using FFBNN technology. First the palm leaf manuscripts characters are segmented by exploiting the sliding window and adaptive histogram calculation. Afterwards, the...

This article details the work undertaken by the National Library of Australia Newspaper Digitisation Program on identifying and testing solutions to improve OCR accuracy in large scale newspaper digitisation programs. In 2007 and 2008 several different solutions were identified, applied and tested on digitised material now available in the Australian Newspapers Digitisation Program beta service...

According to the features of RMB banknote images, combining digital image processing and pattern recognition, this paper proposes a recognition method of RMB word numbers based on character features. The recognition algorithms include: image preprocessing, number region location, feature extraction and character recognition. The experimental results show that the automatic number identification...

The availability of a large sample database is very important to design high accuracy classifiers for handwritten character recognition. Collecting image samples from human writers and practical documents is expensive particularly for large character sets, like with East-Asia-languages. We can therefore take advantage of existing on-line databases to generate additional off-line images. This pa...

In this paper, a novel approach for printed character recognition using linear symmetry is proposed. When the conventional character recognition methods such as the arti1cial neural network based techniques are used to recognise Brahmi Sinhala script, segmentation of modi1ed characters into modi1er symbols and basic characters is a necessity but a complex issue. The large size of the character ...