NDLI: Quantitative assessment of capabilities of colour models for pen ink discrimination in handwritten documents

Content Provider	IET Digital Library
Author	Dansena, Prabhat Pal, Rajarshi Bag, Soumen
Abstract	The addition of new words in handwritten documents such as bank cheques, bills, and notes is considered as common crime. Such immoral activities on handwritten documents have a bad effect on the victim in terms of mental and financial loss. For facilitating an impartial judicial process, it is important to differentiate between the used pen inks. Earlier, image processing and pattern recognition-based techniques for pen ink differentiation gained attention among researchers due to their non-destructive nature. Existing techniques use various colour models to represent the colour of pen inks. Thus, it is crucial to assess the capabilities of various colour models for differentiating pen inks in handwritten documents. In this paper, we propose a histogram distance based quantitative assessment technique for suitable colour model identification for differentiating pen inks. Seven blue and seven black pen ink samples are acquired on 112 cheque leaves. The k-means binarisation is used to identify pen ink pixels. Y C b C r colour model has been identified as the best colour model for this task. The statistical features of the ink colours in the identified colour model representation are extracted and a multi-layer perceptron (MLP) classifier validates the capability of the identified colour model for pen ink discrimination.
Starting Page	1594
Ending Page	1604
Page Count	11
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 8, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6616
Journal	IET Image Processing
Publisher Date	2020-01-29
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Black Pen Ink Samples Cheque Processing Colour Model Assessment Task Computer Vision And Image Processing Technique Document Image Processing Document Processing Technique Feature Extraction Financial Computing Handwritten Character Recognition Handwritten Documents Histogram Distance-based Quantitative Assessment Technique Identified Colour Model Image Classification Image Colour Analysis Image Recognition Ink Ink Colours K-means Binarisation Multilayer Perceptron Classifier Multilayer Perceptrons Neural Computing Technique Pen Ink Differentiation Pen Ink Discrimination Pen Ink Pixel Statistical Analysis Statistics YCbCr Colour Model Representation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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