A data base for Arabic handwritten text recognition research

Al‐Maadeed, Somaya; Elliman, Dave; Higgins, Colin

doi:10.1109/iwfhr.2002.1030957

Cited by 73 publications

(40 citation statements)

References 12 publications

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“…The AHDB [20,135] is an offline database of Arabic handwriting together with several pre-processing procedures. It contains Arabic handwritten paragraphs, words and the words used to represent numbers on checks produced by 100 different writers.…”

Section: Arabic Handwriting Database: Ahdbmentioning

confidence: 99%

A comprehensive survey of handwritten document benchmarks: structure, usage and evaluation

Hussain

Raza²,

Siddiqi

et al. 2015

J Image Video Proc.

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Handwriting has remained one of the most frequently occurring patterns that we come across in everyday life. Handwriting offers a number of interesting pattern classification problems including handwriting recognition, writer identification, signature verification, writer demographics classification and script recognition, etc. Research in these and similar related problems requires the availability of handwritten samples for validation of the developed techniques and algorithms. Like any other scientific domain, the handwriting recognition community has developed a large number of standard databases allowing development, evaluation and comparison of different techniques developed for a variety of recognition tasks. This paper is intended to provide a comprehensive survey of the handwriting databases developed during the last two decades. In addition to the statistics of the discussed databases, we also present a comparison of these databases on a number of dimensions. The ground truth information of the databases along with the supported tasks is also discussed. It is expected that this paper would not only allow researchers in handwriting recognition to objectively compare different databases but will also provide them the opportunity to select the most appropriate database(s) for evaluation of their developed systems.

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Section: Arabic Handwriting Database: Ahdbmentioning

confidence: 99%

A comprehensive survey of handwritten document benchmarks: structure, usage and evaluation

Hussain

Raza²,

Siddiqi

et al. 2015

J Image Video Proc.

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“…One such system, developed a decade ago, is AHDB (Arabic Handwritten DataBase), a database containing samples from 100 different writers, including words used for numbers [12]. In 2003 AI-Ohali et al, developed CENPARMI images databases from 3,000 checks and implemented at the Center for Pattern Recognition and Machine Intelligence provided by a banking corporation [13].…”

Section: Historical Backgroundmentioning

confidence: 99%

Skew Detection/Correction and Local Minima/Maxima Techniques for Extracting a New Arabic Benchmark Database

Hamad¹

2015

ijacsa

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Abstract-We propose a set of techniques for extracting a new standard benchmark database for Arabic handwritten scripts. Thresholding, filtering, and skew detection/correction techniques are developed as a pre-processing step of the database. Local minima and maxima using horizontal and vertical histogram are implemented for extracting the script elements of the database. Elements of the database contain pages, paragraphs, lines, and characters. The database divides into two major parts. The first part represents the original elements without modifications; the second part represents the elements after applying the proposed techniques. The final database has collected, extracted, validated, and saved. All techniques are tested for extracting and validating the elements. In this respect, ACDAR proposes a first issue of the Arabic benchmark databases. In addition, the paper confirms establishment a specialized research-oriented center refers to learning, teaching, and collaboration activities. This center is called "Arabic Center for Document Analysis and Recognition (ACDAR)" which is similar to other centers developed for other languages such as English.

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“…Table 1 contains some of the most popular Arabic words and phrases used in Arabic letters. The most common phrases were counted manually from one thousand handwritten Arabic letters, while the most common words were taken from previous study [20]. The process of creating the data set proceeded as follows.…”

Section: Data Setmentioning

confidence: 99%

Text‐Dependent Writer Identification for Arabic Handwriting

Al-Maadeed

2012

Journal of Electrical and Computer Engineering

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This paper proposes a system for text-dependent writer identification based on Arabic handwriting. First, a database of words was assembled and used as a test base. Next, features vectors were extracted from writers' word images. Prior to the feature extraction process, normalization operations were applied to the word or text line under analysis. In this work, we studied the feature extraction and recognition operations of Arabic text on the identification rate of writers. Because there is no well-known database containing Arabic handwritten words for researchers to test, we have built a new database of offline Arabic handwriting text to be used by the writer identification research community. The database of Arabic handwritten words collected from 100 writers is intended to provide training and testing sets for Arabic writer identification research. We evaluated the performance of edge-based directional probability distributions as features, among other characteristics, in Arabic writer identification. Results suggest that longer Arabic words and phrases have higher impact on writer identification.

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A data base for Arabic handwritten text recognition research

Cited by 73 publications

References 12 publications

A comprehensive survey of handwritten document benchmarks: structure, usage and evaluation

A comprehensive survey of handwritten document benchmarks: structure, usage and evaluation

Skew Detection/Correction and Local Minima/Maxima Techniques for Extracting a New Arabic Benchmark Database

Text‐Dependent Writer Identification for Arabic Handwriting

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