Segmentation of numeric strings

Congedo, G.; Dimauro, Giovanni; Impedovo, S.; Pirlo, Giuseppe

doi:10.1109/icdar.1995.602080

Cited by 61 publications

(38 citation statements)

References 4 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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“…It these segments are not recognized, then different merging strategies are tested. This approach is similar to the strategy proposed by Congedo [15] and Dimauro [17] that also alternates between segmentation and recognition; however their systems lack the ability to correct fragmented digits.…”

Section: Segmentation Main Loopmentioning

confidence: 99%

“…More often, the images are divided into digits using structure-based techniques [51,15,17] and then recognized as individual characters;…”

Section: Segmentation Modulementioning

confidence: 99%

Reading Courtesy Amounts on Handwritten Paper Checks

2002

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In spite of the rapid advances in computers and communication technologies, a number of large-scale applications continue to rely heavily on the use of paper as the dominant medium, either in an intra-organizational or an inter-organizational environment. One major example of this category of paper intensive applications is the check processing application. In a number of countries, the value of each check is read by human eyes before the check is physically transported, in stages, from the point it was presented to the location of the branch of the bank which issued the blank check to the concerned account holder. This process of manual reading of each check involves significant time and cost. In this paper, a new approach is proposed to read the numerical amount field on the check; this field is also called the courtesy amount field. In the case of check processing, the segmentation of unconstrained strings into individual digits is a challenging task because one needs to accommodate special cases involving: connected or overlapping digits, broken digits, and digits physically connected to a piece of stroke that belongs to a neighboring digit. The system described in this paper involves three stages: the segmentation of the string into a series of individual characters; the normalization of each isolated character; and the recognition of each character based on a neural network classifier.

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“…14,15 Since dollar amounts are strings of variable length, the algorithms used to recognize zip codes cannot be applied directly to bank checks. Nevertheless, there are some restrictions on the number of characters between commas and periods.…”

Section: Segmentation Of Courtesy Amountmentioning

confidence: 99%

Handwritten Bank Check Recognition of Courtesy Amounts

Hielscher

Gupta

Wang

2004

Int. J. Image Grap.

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In spite of rapid evolution of electronic techniques, a number of large-scale applications continue to rely on the use of paper as the dominant medium. This is especially true for processing of bank checks. This paper examines the issue of reading the numerical amount field. In the case of checks, the segmentation of unconstrained strings into individual digits is a challenging task because of connected and overlapping digits, broken digits, and digits that are physically connected to pieces of strokes from neighboring digits. The proposed architecture involves four stages: segmentation of the string into individual digits, normalization, recognition of each character using a neural network classifier, and syntactic verification. Overall, this paper highlights the importance of employing a hybrid architecture that incorporates multiple approaches to provide high recognition rates.Keywords: Handwritten checks; Reading of unconstrained handwritten material; neural network based reading; automation of banking systems.

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Segmentation of numeric strings

Cited by 61 publications

References 4 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

Reading Courtesy Amounts on Handwritten Paper Checks

Handwritten Bank Check Recognition of Courtesy Amounts

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