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 Segmentation Based Online Word Recognition: A Conditional ...
unconstrained cursive handwritten English words. In contrast to popular dynamic programming or HMM-based approaches we propose a Conditional Random Field (CRF) driven beam search strategy applied in a combined segmentation-and-recognition framework. First, a candidate segmentation lattice is built using over-segmented primitives of the word ......
AN ARTIFICIAL NEURAL NETWORK BASED SEGMENTATION ALGORITHM ...
segmentation points in printed and joined handwritten words. The algorithm checks for minima in cursive handwriting along with other important features to find segmentation points between characters. An Artificial Neural Network trained with valid segmentation points from a database of scanned, handwritten words is used to assess the correctness...
Cursive Overlapped Character Segmentation: An Enhanced ...
confidence-based segmentation for cursive handwriting recognition”. In Proceeding of 5th International Conference on Simulated Evolution And Learning (SEAL '04), Busan, Korea, SWA-8, 2004. [63] Cheng, C.K. M. Blumenstein, M. “Improving the segmentation of cursive handwritten words using ligature detection and neural validation”....
Lexicon reduction using key characters in cursive ...
The concept of key characters in a cursively handwritten word image is introduced and a method for extracting the key characters is presented. Key characters capture the unambiguous parts of the cursive words that can be reliably segmented and recognized. We propose a method for lexicon reduction using key characters in conjunction with a word-length estimation....
Cursive Multilingual Characters Recognition Based on Hard ...
character segmentation algorithm and neural validation of the segmentation points. For the fair comparison, patterns are selected from the benchmark database. A few grayscale cursive handwritten samples for character segmentation, training, and testing of the BPN are shown in Figure 1. Fig 1. Samples of multilingual images...
A new watershed model based system for character ...
A. Khan, D. Rand MuhammadA simple segmentation approach for unconstrained cursive handwritten words in conjunction with the neural network Int J Image Process, 2 (3) (2008), pp. 29-35 Google Scholar...
On-line handwritten word recognition : An approach based ...
Recognising lines of unconstrained handwritten text is a challenging task. The difficulty of segmenting cursive or overlapping characters, combined with the need to exploit surrounding context, has led to low recognition rates for even the best current recognisers.
H-WordNet: a holistic convolutional neural network ...
A holistic approach effectively tackles such issues by avoiding the character-level segmentation and the earlier holistic methods have been mostly developed using multi-stage machine learning architecture. In this study, a deep convolutional neural network-based holistic method termed ‘H-WordNet’ is proposed for handwritten word recognition....
RNN based online handwritten word recognition in ...
This article proposes a novel approach for online handwritten cursive and non-cursive word recognition in two of the most popular Indian scripts—Devanagari and Bengali, based on two recently developed versions of Recurrent Neural Network (RNN), named as Long–Short Term Memory (LSTM) and Bidirectional Long–Short Term Memory (BLSTM). The proposed approach divides each word horizontally ......
List of Open Access publications for International Journal ...
Segmentation of Handwritten Text in Gurmukhi Script Rajiv K. Sharma, Amardeep Singh Pages - 12 - 17 | Revised - 06-08-2008 | Published - 16-09-2008
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