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Character recognition is one of the fields of research in pattern recognition. Recognition of hand-written characters can be done either On-line or Offline. Not much substantial work has been published in the past on the development of hand-written character recognition (HWCR) systems for Telugu text. However none of them give 100% accuracy in recognition of Telugu characters. Therefore, it is an...
The present work demonstrates a novel scheme for recognising Bengali handwritten consonants by exploring the primitive set of strokes that construct the characters. The Bengali consonants are first manually analysed in order to decompose them into their constituent pattern primitives. Once an exhaustive list of such primitives are prepared, a scheme based on mathematical morphology is devised to identify...
Preserving old archives with readable and editable structure helps people to gain additional experience. Tulu is one of five noteworthy Dravidian dialect with numerous Tulu historical documents which are available within handwritten form. Tulu scripts are rich in patterns with many combinations of connected characters. Henceforth, machine recognition is a major challenge. Till now, no strategy is...
Rising admissions in the South African institutions of higher education have enlarged student-to-lecturer ratios and increased the lecturer's workload, already burdened by administrative tasks. After marking tests, lecturers usually fill in a document called the cover page where the student's number, name and marks according to the questions are placed. Once this is done, they will have to recopy...
We present a framework for handwritten Bangla digit recognition using Sparse Representation Classifier. The classifier assumes that a test sample can be represented as a linear combination of the train samples from its native class. Hence, a test sample can be represented using a dictionary constructed from the train samples. The most sparse linear representation of the test sample in terms of this...
Handwritten character recognition is the key technique in correcting assignment system as well as development of aided instruction software. Considering the disparity in distribution of the pixel, we propose a distribution-based algorithm for handwritten character recognition. Based on the theory of Image Segmentation, the centroid of a character can be found. Around this centroid, the image is divided...
Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. In this paper an attempt is made to recognize handwritten characters for English alphabets without feature extraction...
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...
A new method is used for character segmentation from cursive Arabic words. The method is based on statistical approach which uses Normalization and rectification, coordinate transformation and clustering to extract ligatures. The output is then filtered to extract start, overlapped and end segment errors. After applying the filter the characters are completely isolated and ready for recognition. The...
The old documents in Jawi script are being used widely for references. The hard copies of those scripts will deteriorate as time passes. Most of the previous works on Jawi documents focused on the character recognition and the accuracy of the algorithm was very much affected by noise. An effective preprocessing method is required to binarize degraded Jawi document. In this paper, a new technique to...
Optical Character Recognition (OCR) converts images of handwritten or printed text captured by camera or scanner into editable text. OCR has seen limited adoption in mobile platforms due to the performance constraints of these systems. Intel® Atom™ processors have enabled general purpose applications to be executed on handheld devices. In this paper, we analyze a reference implementation of the OCR...
A presentation on attempt to extract words from handwritten text lines in Gujarati script is hereby submitted. The very cursive nature of most Indian scripts makes the word extraction process a very critical one for Optical Character Recognition (OCR) activity. This cursive nature also causes difficulty during character extraction and modifier extraction. Word extraction is considered as one of the...
This article presents in two modules a new method for segmenting connected handwritten Persian digits using the characteristics of the foreground and utilizing the background skeleton. The first module excavates all the valleys and hills, if there are any, from the upper pixels and lower pixels of the thinned image respectively. Then feature point excavate. For better segmentation the digits, a separability...
In this paper, an improved algorithm is proposed for the segmentation and recognition of handwritten character strings. In the method, a gradient descent mechanism is used to weigh the distance measure in applying KNN for segmenting/recognizing connected characters (numerals and Chinese characters) in the left-to-right scanning direction. In recognizing connected characters, a high quality segmentation...
To recognize unlimited set of handwritten Arabic words, an efficient segmentation algorithm is needed to segment these cursive words into a limited set of primal graphemes. We propose a rule-based segmentation algorithm that segments cursive words into graphemes through collecting special feature points from the word skeleton. The development of this algorithm is motivated by the need to solve problems...
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...
An unconstrained online handwritten Chinese text lines dataset, SCUT-COUCH Textline_NU, a subset of SCUT-COUCH [1] [2], is built to facilitate the research of unconstrained online Chinese text recognition. Texts for hand copying are sampled from China Daily corpus with a stratified random manner. The current vision of SCUT-COUCH Textline_NU has 8,809 text lines (4,813 lines are collected by touch...
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...
This paper describes the efforts at MILE lab, IISc, to create a 100,000-word database each in Kannada and Tamil for the design and development of Online Handwritten Recognition. It has been collected from over 600 users in order to capture the variations in writing style. We describe features of the scripts and how the number of symbols were reduced to be able to effectively train the data for recognition...
This paper deals with on-line handwriting recognition in a closed-world environment with a large lexicon. Several applications using handwriting recognition have been developed, but most of them consider a lexicon of limited size. Many difficulties, in particular confusions during the segmentation stage, are linked to the use of a large lexicon, with large writing variations and an increased complexity...
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