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Journal ArticleDOI

Performance analysis of character segmentation approach for cursive script recognition on benchmark database

Amjad Rehman, +1 more
- 01 May 2011 - 
- Vol. 21, Iss: 3, pp 486-490
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TLDR
This paper analyzes the improved performance of the proposed character segmentation algorithm in comparison to others presented in the literature from accuracy and computational complexity points of view and concludes that proposed approach enhances the cursive script segmentation accuracy with minimum computational complexity.
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This article is published in Digital Signal Processing.The article was published on 2011-05-01. It has received 53 citations till now. The article focuses on the topics: Scale-space segmentation & Segmentation-based object categorization.

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Citations
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Medical Image Segmentation Methods, Algorithms, and Applications

TL;DR: The latest segmentation methods applied in medical image analysis are described and the advantages and disadvantages of each method are described besides examination of each algorithm with its application in Magnetic Resonance Imaging and Computed Tomography image analysis.
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Neural networks for document image preprocessing: state of the art

TL;DR: Cl clusters, summarize, interpret and evaluate neural networks in document Image preprocessing, and the importance of the learning algorithms in neural networks training and testing for preprocessing is highlighted.
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Implications of E-learning systems and self-efficiency on students outcomes: a model approach

TL;DR: The results indicated that system quality, information quality, and computer self-efficacy all affected system use, user satisfaction, and self-managed learning behavior of students.
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Computer-assisted brain tumor type discrimination using magnetic resonance imaging features.

TL;DR: A comprehensive review of recent research on brain tumors multiclass classification using MRI is provided and a set of recommendations for researchers and professionals working in the area of brain tumors classification is provided.
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Methods and strategies on off-line cursive touched characters segmentation: a directional review

TL;DR: This paper is the first survey that focuses on touched character segmentation and provides segmentation rates, descriptions of the test data for the approaches discussed, and the main trends in the field of touched character segmentsation.
References
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Journal ArticleDOI

A database for handwritten text recognition research

TL;DR: An image database for handwritten text recognition research is described that contains digital images of approximately 5000 city names, 5000 state names, 10000 ZIP Codes, and 50000 alphanumeric characters to overcome the limitations of earlier databases.
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The IAM-database: an English sentence database for offline handwriting recognition

TL;DR: A database that consists of handwritten English sentences based on the Lancaster-Oslo/Bergen corpus, which is expected that the database would be particularly useful for recognition tasks where linguistic knowledge beyond the lexicon level is used.
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A survey of methods and strategies in character segmentation

TL;DR: H holistic approaches that avoid segmentation by recognizing entire character strings as units are described, including methods that partition the input image into subimages, which are then classified.
Journal ArticleDOI

Optical character recognition for cursive handwriting

TL;DR: A new analytic scheme, which uses a sequence of image segmentation and recognition algorithms, is proposed for the off-line cursive handwriting recognition problem and indicates higher recognition rates compared to the available methods reported in the literature.
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