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International Journal of Multimedia Information Retrieval

Erschienen in:

29.07.2017 | Trends and Surveys

Script identification algorithms: a survey

verfasst von: Parul Sahare, Sanjay B. Dhok

Erschienen in: International Journal of Multimedia Information Retrieval | Ausgabe 3/2017

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Abstract

Script identification is being widely accepted techniques for selection of the particular script OCR (Optical Character Recognition) in multilingual document images. Extensive research has been done in this field, but still it suffers from low identification accuracy. This is due to the presence of faded document images, illuminations and positions while scanning. Noise is also a major obstacle in the script identification process. However, it can only be minimized up to a level, but cannot be removed completely. In this paper, an attempt is made to analyze and classify various script identification schemes for document images. The comparison is also made between these schemes, and discussion is made based upon their merits and demerits on a common platform. This will help the researchers to understand the complexity of the issue and identify possible directions for research in this field.

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Titel: Script identification algorithms: a survey
verfasst von: Parul Sahare
Sanjay B. Dhok
Publikationsdatum: 29.07.2017
Verlag: Springer London
Erschienen in: International Journal of Multimedia Information Retrieval / Ausgabe 3/2017
Print ISSN: 2192-6611
Elektronische ISSN: 2192-662X
DOI: https://doi.org/10.1007/s13735-017-0130-2

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Unsupervised group feature selection for media classification

Computational framework for emotional VAD prediction using regularized Extreme Learning Machine

ACM International Conference on Multimedia Retrieval (ICMR): current standing and impact

An overview of traffic sign detection and classification methods

DBAHCL: database for Arabic handwritten characters and ligatures

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