A new segmentation approach for handwritten digits

Oliveira, L. E. S. de; Lethelier, E.; Bortolozzi, Flávio; Sabourin, Robert

doi:10.1109/icpr.2000.906078

Cited by 17 publications

(20 citation statements)

References 8 publications

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“…With the manual verification of the segmentation, 96.66% of digits were successively segmented. Besides, TABLE III gives the performance comparison between ours and several successive algorithms described in other literatures: traditional Drop-fall algorithm (DF) [6], algorithm of distance difference from upper contour to lower contour (DD) [7] and foreground analysis algorithm (FA) [8]. By using our strategy 95.6% of touching digits were correctly segmented exceeding the other algorithms, and recognition accuracy is increased consequently.…”

Section: Methodsmentioning

confidence: 98%

An Approach of Removing Stroke Based on Touching Pattern for Handwritten Digits Segmentation

Ma¹,

Cheng²,

Gu³

2013

Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information

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-For finding precise segmentation, a new approach to remove and amend stroke connecting touching handwriting digits based on touching pattern is presented. Firstly, background region of touching digits is analyzed by using water reservoirs concept, and then the classification scheme is developed to identify the pattern of touching digits according to the structural features. In single-point touching type, two touching pairs of digits can be connected with a ligature, which can be a component of one of the digits or belong to no digit. After segmentation is performed to get isolated digits. the pattern-oriented ligature analysis investigates whether candidate ligature is a part of digit or a useless stroke and decides to be preserved or be removed. Experimental results show that the proposed approach is effective for segmentation of handwritten touching digits and segmentation errors have been reduced.

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Section: Methodsmentioning

confidence: 98%

An Approach of Removing Stroke Based on Touching Pattern for Handwritten Digits Segmentation

Ma¹,

Cheng²,

Gu³

2013

Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information

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“…Oliveira et al [6] put forward a recognition-based segmentation algorithm. It uses the combination of two complementary sets of structural features, namely, contour/ profile and skeletal points.…”

Section: Recognition-based Segmentationmentioning

confidence: 99%

“…Numerous techniques are available for segmentation of handwritten connected digits [1,[3][4][5][6][7][8][9][10][11][12][13][14][15][16]. R.G.…”

Section: Introductionmentioning

confidence: 99%

An overview of segmentation techniques for handwritten connected digits

Kulkarni

Vasambekar

2010

2010 International Conference on Signal and Image Processing

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Machine recognition of handwritten numerals has practical significance. Segmentation of connected digits is being recognized as a critical task in the field of document image analysis and recognition. Higher recognition rates for isolated digits Vs those obtained for connected numeral strings exemplify the vital role of connected digits segmentation. The present overview describes various segmentation techniques for connected digits in general numeral strings and mathematical expressions, worked out in this decade.

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“…9 Various segmentation algorithms have been proposed based on the morphology of the connected digits for¯nding one or multiple interconnection points, 9 which are based on the contour, 15-17 the skeleton 18-20 and the reservoir 21 or by combining simultaneously the contour, pro¯le and the skeleton. 8,22 More recently, these algorithms have been compared objectively using synthetic and real connected digits. 9 In the following, we brie°y review the most popular algorithms to segment two connected digits according to the type of the morphology for detecting the cutting path.…”

Section: Introductionmentioning

confidence: 99%

SVM-Based Segmentation-Verification of Handwritten Connected Digits Using the Oriented Sliding Window

Gattal

Chibani

2015

Int. J. Comp. Intel. Appl.

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We propose in this paper a system to recognize handwritten digit strings, which constitutes a di±cult task because of overlapping and/or joining of adjacent digits. To resolve this problem, we use a segmentation-veri¯cation of handwritten connected digits based conjointly on the oriented sliding window and support vector machine (SVM) classi¯ers. The proposed approach allows separating adjacent digits according the connection con¯guration by¯nding at the same time the interconnection points between adjacent digits and the cutting path. SVM-based segmentation-veri¯cation using the global decision module allows the rejection or acceptance of the processed image. Experimental results conducted on a large synthetic database of handwritten digits show the e®ective use of the oriented sliding window for segmentationveri¯cation.

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A new segmentation approach for handwritten digits

Cited by 17 publications

References 8 publications

An Approach of Removing Stroke Based on Touching Pattern for Handwritten Digits Segmentation

An Approach of Removing Stroke Based on Touching Pattern for Handwritten Digits Segmentation

An overview of segmentation techniques for handwritten connected digits

SVM-Based Segmentation-Verification of Handwritten Connected Digits Using the Oriented Sliding Window

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