Call For Paper Volume:4 Issue:10 Oct'2017 |

CONTENT RECOVERY AND IMAGE RETRIVAL IN IMAGE DATABASE

Publication Date : 31/12/2014



Author(s) :

K.YUVASRI , B.ARULKUMAR , S.SYED FARMHAN.


Volume/Issue :
Volume 1
,
Issue 6
(12 - 2014)



Abstract :

Digital Images are used in magazines, blogs, website, television and more. Digital image processing techniques are used for feature selection, pattern extraction classification and retrieval requirements. Color, texture and shape features are used in the image processing. Digital images processing also supports computer graphics and computer vision domains. Scene text recognition is performed with two schemes. They are character recognizer and binary character classifier models. A character recognizer is trained to predict the category of a character in an image patch. A binary character classifier is trained for each character class to predict the existence of this category in an image patch. Scene text recognition is performed on detected text regions. Pixel-based layout analysis method is adopted to extract text regions and segment text characters in images. Text character segmentation is carried out with color uniformity and horizontal alignment of text characters. Discriminative character descriptor is designed by combining several feature detectors and descriptors. Histogram of Oriented Gradients (HOG) is used to identify the character descriptors. Character structure is modeled at each character class by designing stroke configuration maps. The scene text extraction scheme is also supports for smart mobile devices. Text recognition methods are used with text understanding and text retrieval applications. The text recognition scheme is enhanced with content based image retrieval process. The system is integrated with additional representative and discriminative features for text structure modeling process. The system is enhanced to perform text and word level recognition using lexicon analysis. The training process is included with word database update task.


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CONTENT RECOVERY AND IMAGE RETRIVAL IN IMAGE DATABASE

December 11, 2014