Extraction and analysis of forensic document examiner features used for writer identification

Pervouchine, Vladimir; Leedham, Graham

doi:10.1016/j.patcog.2006.08.008

Cited by 92 publications

(55 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Writer recognition systems can typically make use of global features such as texture, curvature and slant features [10][11][12] as well as a combination of local features such as graphemes, allographs and connected components [1,13,14] Our work falls into the latter category of text-independent techniques where the writers are not bounded by any specific lines of text in order for the system to recognize them. Instead, the system analyzes their handwriting styles through a series of automated processes, regardless of what they have written.…”

Section: Previous Workmentioning

confidence: 99%

Automatic writer identification framework for online handwritten documents using character prototypes

Tan

Viard-Gaudin

Kot

2009

Pattern Recognition

View full text Add to dashboard Cite

This paper proposes an automatic text-independent writer identification framework that integrates an industrial handwriting recognition system, which is used to perform an automatic segmentation of an online handwritten document at the character level. Subsequently, a fuzzy c-means approach is adopted to estimate statistical distributions of character prototypes on an alphabet basis. These distributions model the unique handwriting styles of the writers. The proposed system attained an accuracy of 99.2% when retrieved from a database of 120 writers. The only limitation is that a minimum length of text needs to be present in the document in order for sufficient accuracy to be achieved. We have found that this minimum length of text is about 160 characters or approximately equivalent to 3 lines of text. In addition, the discriminative power of different alphabets on the accuracy is also reported.

show abstract

Section: Previous Workmentioning

confidence: 99%

Automatic writer identification framework for online handwritten documents using character prototypes

Tan

Viard-Gaudin

Kot

2009

Pattern Recognition

View full text Add to dashboard Cite

show abstract

“…This has led to lesser MAE value for intra-class while the MAE value for the interclass becomes larger, evidencing the practicability of the proposed technique in features extraction in the context of TI. Additionally, the notion of individuality relating to twin handwriting-fingerprint has been mentioned in several works including Eliabeth et al (2015) and Pervouchine and Leedham (2007). Some empirical validation of individuality of twin multi-biometric with the AUMI algorithm of MF in the extraction of feature is offered in this work.…”

Section: Experiments Resultsmentioning

confidence: 99%

A Multimodal Biometric System using Global Features for Identical Twins Identification

Mohammed

Shamsuddin

2018

Journal of Computer Science

View full text Add to dashboard Cite

Pattern recognition studies are currently focusing on twin's biometric identification. The system of twins' biometric Identification can potentially differentiate the individual's biometric pattern. With the new Unimodal biometric identification, identical twins are precisely and reliably identified, with well exposure of certain traits. However, it is much more challenging to identify identical twins as they share so many similarities between them, as opposed to identifying the non-twins. Therefore, this study proposes the use of more than one biometric trait with global features. Pattern recognition application includes extracting and selecting meaningful features and this has brought to the key question in twin handwriting-fingerprint identification: How to obtain features from many writing styles and shapes of twin handwritingfingerprint in order that the reflection of the right person between twins can be obtained. Global with Aspect United Moment Invariant for the extractions of global feature using the identical twin multi-biometric identification is thus proposed by this study.

show abstract

“…In 2007, Vladimir Pervouchine et al [34] implemented a writer identification scheme based on high frequent characters. In this method, the high frequent characters (‗f','d','y','th') are first identified, and then according to the similarity of those characters, the writer is selected.…”

Section: Chinese English and Other Languagesmentioning

confidence: 99%

A Survey on Writer Identification Schemes

Sreeraj¹,

Idicula²

2011

IJCA

View full text Add to dashboard Cite

This paper presents a survey of the literature on writer identification schemes and techniques up till date. The paper outlines an overview of the writer identification schemes mainly in Chinese, English, Arabic and Persian languages. Taxonomy of different features adopted for online and offline writer identification schemes is also drawn at. The feature extraction methods adopted for the schemes are discussed in length outlining the merits and demerits of the same. In automated writer identification, text independent and text dependent methods are available which is also discussed in this paper. An evaluation of writer identification schemes under multiple languages is also analyzed by comparing the recognition rate.

show abstract

Extraction and analysis of forensic document examiner features used for writer identification

Cited by 92 publications

References 9 publications

Automatic writer identification framework for online handwritten documents using character prototypes

Automatic writer identification framework for online handwritten documents using character prototypes

A Multimodal Biometric System using Global Features for Identical Twins Identification

A Survey on Writer Identification Schemes

Contact Info

Product

Resources

About