Writer identification using edge-based directional features

Bulacu, M.; Schomaker, Lambert; Vuurpijl, L.G.

doi:10.1109/icdar.2003.1227797

Cited by 131 publications

(81 citation statements)

References 6 publications

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“…In addition, writer identification has been performed by a textualbased information retrieval model. The work in [25] presented a new approach using a connected-component contour codebook and its probability density function. In addition, combining connected-component contours with an independent edge-based orientation and curvature PDF yields very high correct identification rates.…”

Section: A Review Of Related Workmentioning

confidence: 99%

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

Al-Maadeed

Ferjani

Elloumi

et al. 2016

J Image Video Proc.

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A challenging area of pattern recognition is the recognition of handwritten texts in different languages and the reduction of a volume of data to the greatest extent while preserving associations (or dependencies) between objects of the original data. Until now, only a few studies have been carried out in the area of dimensionality reduction for handedness detection from off-line handwriting textual data. Nevertheless, further investigating new techniques to reduce the large amount of processed data in this field is worthwhile. In this paper, we demonstrate that it is important to select only the most characterizing features from handwritings and reject all those that do not contribute effectively to the process of handwriting recognition. To achieve this goal, the proposed approach is based mainly on fuzzy conceptual reduction by applying the Lukasiewicz implication. Handwritten texts in both Arabic and English languages are considered in this study. To evaluate the effectiveness of our proposal approach, classification is carried out using a K-Nearest-Neighbors (K-NN) classifier using a database of 121 writers. We consider left/right handedness as parameters for the evaluation where we determine the recall/precision and F-measure of each writer. Then, we apply dimensionality reduction based on fuzzy conceptual reduction by using the Lukasiewicz implication. Our novel feature reduction method achieves a maximum reduction rate of 83.43 %, thus making the testing phase much faster. The proposed fuzzy conceptual reduction algorithm is able to reduce the feature vector dimension by 31.3 % compared to the original "BEST OF ALL COMBINED FEATURES" algorithm.

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Section: A Review Of Related Workmentioning

confidence: 99%

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

Al-Maadeed

Ferjani

Elloumi

et al. 2016

J Image Video Proc.

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“…To study the inheritance pattern of characteristics of handwritings between parents and siblings members of the family i.e. Father, mother and the off-springs (family with two off-springs was selected for the study) [5,6].…”

Section: Volume 5 | Issuementioning

confidence: 99%

A Study to Determine the Inheritance Pattern of Characteristics of Handwriting between Parents and Off-springs

Kiran¹,

Sridhar²

2017

Journal of Forensic Science & Criminology

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“…To reduce the computational cost suffered by 2-D Gabor filters, He et al [9] further introduced a contourlet method to handwriting identification. In [10], edge-based directional probability distributions were used as features; meanwhile charactershape (allograph) is another type of effective feature [2]. In [15], the feature vector was derived by Copyright morphologically processing the horizontal profiles of the words, where the projections were derived and processed in segments to increase the discriminating power.…”

Section: A Related Workmentioning

confidence: 99%

A Stroke Shape and Structure Based Approach for Off-line Chinese Handwriting Identification

Tan¹,

Lai²,

Wang³

et al. 2011

IJISA

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Writer identification using edge-based directional features

Cited by 131 publications

References 6 publications

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

A Study to Determine the Inheritance Pattern of Characteristics of Handwriting between Parents and Off-springs

A Stroke Shape and Structure Based Approach for Off-line Chinese Handwriting Identification

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