TY - JOUR
AU - 
AB - Objectives: To reduce false positive rate of text localization and to improve the performance of image segmentation process for better detection of text in images. Methods: Text information in images is an important consideration for image based applications such as automatic geo coding, content based image retrieval and understanding scene. But to detect the text from a complex background with different colours is a complex task. There are different techniques has been proposed to detect text in images. One of the techniques is hybrid approach for text localization and text detection in natural scene images. In this approach, the text region detector is used to detect text region and to segment the candidate components by local binarization. Then the non text components are filtered using Conditional Random Field model (CRF). Finally the text components are grouped together as line or words. This approach feels hard to segment some complex images due to lack of colour information. In order to enhance the performance of text detection in images Mahalanobis Distance (MD) metric, cosine based similarity metric and text recognition is introduced. Findings: The Mahalanobis Distance (MD) metric, cosine based similarity metric are computed for image segmentation process where colour information 
TI - An Efficient Approach for the Identification and Localization of Texts in Images
JF - Indian Journal of Science and Technology
DO - 10.17485/ijst/2017/v10i17/112354
DA - 2017-05-01
UR - https://www.deepdyve.com/lp/unpaywall/an-efficient-approach-for-the-identification-and-localization-of-texts-Uu3ReZCH0L
DP - DeepDyve
ER -