Publication

A New Method of Contrast Normalization for Verification of Extracted Video Text Having Complex Backgrounds

2002
Reports

Abstract

One of the difficulties of extracting text contained in images or videos comes from the variation of the grayscale values of the text and backgrounds. In this paper we propose a new method to normalize the contrast between text characters and backgrounds so that a trained machine learning tool can verify characters of grayscale values that have never been seen before. Experiments show that the proposed method used in training either a multilayer perceptrons or a support vector machine yields better text verification comparing with other typical contrast measures.

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2002
Reports

Abstract

Official source

Related concepts (32)

Text mining

Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al.

Machine learning

Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.

Support vector machine

In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Developed at AT&T Bell Laboratories by Vladimir Vapnik with colleagues (Boser et al., 1992, Guyon et al., 1993, Cortes and Vapnik, 1995, Vapnik et al., 1997) SVMs are one of the most robust prediction methods, being based on statistical learning frameworks or VC theory proposed by Vapnik (1982, 1995) and Chervonenkis (1974).

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A New Method of Contrast Normalization for Verification of Extracted Video Text Having Complex Backgrounds

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