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Proceedings of

International Conference on Advances in Image Processing and Computation Techniques PCT 2012

Date
14-Jul-2012
Location
singapore , United Kingdom
Authors
5
ISBN
978-981-07-2969-1

3 Articles Published

1. FEATURE LEVEL FUSION FOR ONLINE ARABIC SCRIPT BASED LANGUAGES CHARACTER RECOGNITION

Authors: MUHAMMAD IMRAN RAZZAK , MOHAMMED TALAL SIMSIM

Abstract: Arabic script character recognition remains a challenging task due to its cursive nature. The aim of feature extraction from the input strokes reduces the input pattern to avoid complexities while maintaining the high accuracy. Feature extraction in pattern recognition problems involves the extraction of unique and salient patterns from the preprocessed data in order to enhance the discriminatory power and reduce the data for classification and it is crucial for the success of recognition system. We proposed feature level fusion for Arabic character recognition. We extracted structural and directional features for handwritten stroke and fused these feature to form more discriminant feature matrix. The feature level fusion for handwritten character recognition provides considerable gain in accuracy. The fusion of feature is also suitable for other handwritten tasks i.e. personality determination, writer identification where the more variations are required

Keywords: Feature Extraction, Arabic Character Recognition, Feature Fusion

Pages: 1 - 5 | DOI: 10.15224/978-981-07-2969-1-123

2. DE-NOISING FILTER FOR IMPULSE NOISE IN GLACIER ICE INFRARED IMAGES

Authors: P. SUBASHINI

Abstract: different temperature range and also captures better quality images during night time. Infrared Thermography is an emerging technology for nondestructive testing. So infrared images are considered to identify and classify ice types of river ice. However, it is subject to blurring and degradation of the acquired signal, as the diffusive nature in the process. This makes difficulties for qualitative and quantitative analyses, especially when deeper defects which are located within the substrate, as well as high thermal conductivity materials are inspected. The IR images usually have noise, edges, text information and small objects of interest. Non linear filters such as standard median filter however often tends to remove fine details in the image, such as thin lines and corners. So to overcome the drawback of median filter, relaxed median filter, adaptive median filter, decision based median filter and untrimmed decision based median filters are used for denoising. The results of all th

Keywords: De-noising, infrared image, median filter, relaxed median filter, adaptive median filter, decision based median filter and UDBMF.

Pages: 6 - 10 | DOI: 10.15224/978-981-07-2669-1-140

3. BLOGS SEARCH ENGINE USING RSS SYNDICATION AND FUZZY PARAMETERS

Authors: ATHRAA JASIM MOHAMMED , HUSNIZA HUSNI

Abstract: The rapid development of the internet eventually increases the number of internet users triggering the need for an intelligent search engine that is able to minimize the search on world wide web (WWW) and find relevant information as requested. To overcome the issue of finding relevant information as well as minimizing the search on WWW, this paper proposes a search engine that is specifically designed and built using RSS syndication and fuzzy Parameters to search for information contained in blogs. The blogs search engine consists of three main phases: 1) crawling using RSS feeds algorithm; 2) indexing weblogs algorithm; and 3) searching technique using fuzzy logic. In RSS crawling process, the RSS feeds need to be gathered to extract useful information such as title, links, time published, and description. Next, indexing weblogs uses the links to retrieve the blog sites for text processing and for constructing the indexing database. In order to retrieve such information requested or

Keywords: Rss feeds, blog ssearch engine, fuzzy weighted average, keyword density.

Pages: 11 - 15 | DOI: 10.15224/978-981-07-2969-1-145

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