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Text recognition has revolutionized the world of image processing and intelligent transportation system (ITS). It opened several possibilities to traditional ITS concept. Advancement in text recognition has made it possible to implement text recognition in ITS. Traffic panel text recognition, a real time application is considered as a key addition to the revolution in modern ITS. This research aims...
This paper addresses the problem of handwritten and printed text separation in Arabic document images. The objective is to extract handwritten text from other parts of the document. This allows the application, in a second time, of a specialized processing on the extracted handwritten part or even on the printed one. Documents are first preprocessed in order to remove eventual noise and correct document...
Now days reading words from an unconstrained and noisy image is not easy. Text localization and recognition in an image is a research area which takes efforts to develop a computer system with an ability to automatically read the text from images. The Optical Character Recognition (OCR) tool gives good results obtained to read the text from an image. The objective of this study is to propose a new...
Resolving ambiguity within mathematical symbols is essential for recognition of mathematical expressions. In this paper, we focus on the resolving ambiguities in mathematical symbols and propose a novel recognition technique that has been tested over large number of ambiguous mathematical symbols obtained from different categories including factoring formula, algebra identity, geometric progression,...
Optical character recognition or OCR becomes necessary first step for all applications that consider typewritten or handwritten manuscripts as input. We need to train our classifier in case we are considering to use data mining techniques for such purposes. There are several established generic classification techniques that can be used together with feature extraction mechanisms but it is important...
Immense analysis has been done on optical character recognition (OCR). Numerous works has stated for English, Chinese, Devanagari, Malayalam, Arabic scripts, etc. Segmentation has imp phase in OCR and various articles have been published on different segmentation methods like Thinning, histogram etc for different script during last few years. Generally there is not work done on Overlapped and touching...
Segmentation of line, word and character are one of the critical phases of optical character recognition (OCR). Due to the imperfection in segmentation, most of the recognition system produce poor recognition rate. In this paper we are discussing some novel approach for line, word and character segmentation of printed Manipuri document. Few works has been done for optical character recognition on...
This paper presents a novel approach for offline Bangla (Bengali) handwritten word recognition by Hidden Markov Model (HMM). Due to the presence of complex features such as headline, vowels, modifiers, etc., character segmentation in Bangla script is not easy. Also, the position of vowels and compound characters make the segmentation task of words into characters very complex. To take care of these...
The generic process of Optical Character Recognition (OCR), an area of intensive research in the field of Artificial Intelligence, Pattern Recognition and Computer Vision, aims to recognize text from scanned document images, where data can be in machine printed or hand written format. Optical Character Recognition can improve the interaction between man and machine in various applications including...
Recognition of Bangla compound characters has rarely got attention from researchers. This paper deals with segmentation and recognition of online handwritten Bangla cursive text containing basic and compound characters and all types of modifiers. Here, at first, we segment cursive words into primitives. Next primitives are recognized. A primitive may represent a character/compound character or a part...
Offline handwritten text recognition is a very challenging problem. Aside from the large variation of different handwriting styles, neighboring characters within a word are usually connected, and we may need to segment a word into individual characters for accurate character recognition. Many existing methods achieve text segmentation by evaluating the local stroke geometry and imposing constraints...
Automatic extraction of date patterns from handwritten document involves difficult challenges due to writing styles of different individuals, touching characters and confusion among identification of alphabets and digits. In this paper, we propose a framework for retrieval of date patterns from handwritten documents. The method first classifies word components of each text line into month and non-month...
The large amount of Myanmar document images are getting archived by the Digital Libraries, an efficient strategy is needed to convert document image into machine understandable text format. The state of the art OCR systems can't do for Myanmar scripts as our language pose many challenges for document understanding. Therefore, this paper plans an OCR system for Myanmar Printed Document (OCRMPD) with...
This paper addresses the problem of binalizing multicolored character strings in scene images subject to heavy image degradations and complex backgrounds. The proposed method consists of four steps. The first step generates tentatively binarized images via every dichotomization of K clusters obtained by K-means clustering of constituent pixels of a given image in the HSI color space. The total number...
We proposed a new process strategy for on-line handwriting Chinese Character recognition and applied it to overlapping samples. On one hand, those samples are evaluated on stroke level by support vector machine, on the other hand, we do character level evaluation basing on a character pair search model. Then a merging strategy was proposed to filter out correct segmentation positions. We test our...
As large quantity of document images is getting archived by the digital libraries, an efficient strategy that can convert Myanmar document image into machine understandable text format is needed. And Myanmar language contains many words, and most of them are similar, especially for small fonts, the accuracy of the Optical Character Recognition, OCR system for Myanmar may be low. Therefore, this paper...
In India, more than 300 million people use Devanagari script for documentation. There has been a significant improvement in the research related to the recognition of printed as well as handwritten Devanagari text in the past few years. State of the art from 1970s of machine printed and handwritten Devanagari optical character recognition (OCR) is discussed in this paper. All feature-extraction techniques...
Handwritten character recognition has received extensive attention in academic and production fields. The recognition system can be either on-line or off-line. Off-line handwriting recognition is the subfield of Optical Character Recognition . In this paper, We introduce the fundamental principles of Chinese handwritten numerals, including digital image preprocessing, segmentation, features extraction...
This paper presents a character recognition system that handles degraded manuscript documents like the ones discovered at the St. Catherine's Monastery. In contrast to state-of-the-art OCR systems, no early decision (image binarization) needs to be performed. Thus, an object recognition methodology is adapted for the recognition of ancient manuscripts. The proposed system is based on local descriptors...
The hierarchical nature of Chinese characters has inspired radical-based recognition, but radical segmentation from characters remains a challenge. We previously proposed a radical-based approach for on-line handwritten Chinese character recognition, which incorporates character structure knowledge into integrated radical segmentation and recognition, and performs well on characters of left-right...
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