Character segmentation in handwritten words — An overview

Lu, Yi; Shridhar, M.

doi:10.1016/0031-3203(95)00072-0

Cited by 136 publications

(47 citation statements)

References 10 publications

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“…In the last decade of the previous century, DT found their way to applications such as route planning [61] and (robot) navigation [26], collision prevention [27], handwriting recognition [62], image segmentation [9] (see also Fig. (1)), skeletonization [63], Voronoi tessellations [30,64], Watershed algorithms [65], and MRI data analysis [66].…”

Section: On More Than 30 Years Of Researchmentioning

confidence: 99%

“…On the other hand, they are applied within various applications; see for example, [53,69,91]. In the last case, DT are either applied by themselves or as an intermediate method such as: route planning and (robot) navigation [26,28,56,61,70], collision prevention [27], video surveillance [69,71], internal radiation therapy [13], handwriting recognition [62,72], (medical) image segmentation [9][10][11][13][14][15] (see also Fig. (1)), skeletonization [63,73], Voronoi tessellations [30,64], BouligandMinkowsky fractal dimension [74], Watershed algorithms [65], neuromorphometry [73,75], MRI data analysis [76,92], and volume rendering [36,77], to mention but a few.…”

Section: Current and Future Developmentsmentioning

confidence: 99%

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Distance Transforms: Academics Versus Industry

Broek

Schouten²

2011

CSENG

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Abstract:In image and video analysis, distance transformations (DT) are frequently used. They provide a distance image (DI) of background pixels to the nearest object pixel. DT touches upon the core of many applications; consequently, not only science but also industry has conducted a significant body of work in this field. However, in a vast majority of the cases this has not been published in major scientific outlets but has been filed as a patent application. This article provides a brief introduction into DT, including a specification of a few of the most prominent algorithms in the field. Next, a few interesting algorithms from the last decade are discussed. A benchmark including eight DT algorithms (i.e., city block, Danielsson's algorithm, chamfer 3-4, hexadecagonal region growing, a recent claimed true Euclidean DT, and three exact Euclidean DT) has been executed, which illustrates the intriguing complexity of DT in terms of precision and computational complexity. Subsequently, a selection of key patent applications are discussed that have emerged in this field, including their scientific merit and areas of application. Finally, this article's findings are summarized and discussed, with an emphasis on both the common ground of scientific articles and patent applications as well as the added value they can have to each other.

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Section: On More Than 30 Years Of Researchmentioning

confidence: 99%

Section: Current and Future Developmentsmentioning

confidence: 99%

Distance Transforms: Academics Versus Industry

Broek

Schouten²

2011

CSENG

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show abstract

“…Some elaborate studies on text line, word and character segmentation are in [17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Singh¹,

Gupta²,

Tyagi³

2011

IJCA

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Fast and accurate algorithms are necessary for Optical Character Recognition (OCR) systems to perform operations on document images such as pre-processing, segmentation, feature extraction, training and testing of classifiers and post processing. Text line and word segmentation are two important steps in any OCR system. Wrong segmentation may affect the accuracy rate of OCR systems. The segmentation is very challenging in cases of availability of different types of noises, degradations, and variation in writing and script characteristics. However, existing algorithms suffer from a flawed tradeoff between accuracy and speed. In this research work, Devanagri text line and word segmentation are carried out using modified standard profiling based segmentation approach and parallelized it on Graphics Processing Unit (GPU). The main goal of this research work is to make segmentation faster for processing a large number of document images using parallel implementation of algorithms on GPU. GPUs are emerging as powerful parallel systems at a cheaper cost. Our work employs extensive usage of highly multithreaded architecture and shared memory of multi-cored GPU. An efficient use of shared memory is required to optimize parallel reduction in Compute Unified Device Architecture (CUDA). Experimental results show that our method can achieve a speedup of about 20x-30x over the serial implementation when running on a GPU named GeForce 9500 GT having 32 cores.

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“…Pre-segmentation is the process of word segmentation into primitive segments. Many algorithms have been proposed for this task and we recommend two surveys that review this field [52] and [8]. In the case of a segmentation-free method, this stage may be ignored or replaced with splitting the image into sequential fragments that do not attempt to match complete characters.…”

Section: Stages In a Word Recognition Systemmentioning

confidence: 99%

“…The reader might be interested in other relevant surveys involving online cursive recognition [82], OCRs [42,84], and segmentation techniques [52,8].…”

Section: Introductionmentioning

confidence: 99%

Offline cursive script word recognition ? a survey

Steinherz

Rivlin

Intrator

1999

International Journal on Document Analysis and Recognition

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Abstract.We review the field of offline cursive word recognition. We mainly deal with the various methods that were proposed to realize the core of recognition in a word recognition system. These methods are discussed in view of the two most important properties of such a system: the size and nature of the lexicon involved, and whether or not a segmentation stage is present. We classify the field into three categories: segmentation-free methods, which compare a sequence of observations derived from a word image with similar references of words in the lexicon; segmentation-based methods, that look for the best match between consecutive sequences of primitive segments and letters of a possible word; and the perception-oriented approach, that relates to methods that perform a human-like reading technique, in which anchor features found all over the word are used to bootstrap a few candidates for a final evaluation phase.

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Character segmentation in handwritten words — An overview

Cited by 136 publications

References 10 publications

Distance Transforms: Academics Versus Industry

Distance Transforms: Academics Versus Industry

Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Offline cursive script word recognition ? a survey

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