A novel local enhancement technique for rebuilding Broken characters in a degraded Kannada script

作者: N. Sandhya , R. Krishnan , D. R. Ramesh Babu

DOI: 10.1109/IADCC.2015.7154693

关键词:

摘要: Degraded character recognition is one of the most challenging topic in field Kannada recognition. The degraded characters which are broken and deformed will have missing features be difficult for any method. Rebuilding very important better This paper proposes a novel method to rebuild characters. These thinned endpoints lines obtained. line segments effectively rebuilt so as preserve character. Experimental results on this presented establish its efficiency.

参考文章(7)
Reza Farrahi Moghaddam, Mohamed Cheriet, A Variational Approach to Degraded Document Enhancement IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 32, pp. 1347- 1361 ,(2010) , 10.1109/TPAMI.2009.141
Srikanta Murthy K, Arun Vikas Singh, Restoration of Degraded Historical Document Image ,(2012)
Wafa Boussellaa, Aymen Bougacha, Abderrazak Zahour, Haikal El Abed, Adel Alimi, Enhanced Text Extraction from Arabic Degraded Document Images Using EM Algorithm international conference on document analysis and recognition. pp. 743- 747 ,(2009) , 10.1109/ICDAR.2009.220
Sangeet Aggarwal, Sanjeev Kumar, Ritu Garg, Santanu Chaudhury, None, Content directed enhancement of degraded document images Proceeding of the workshop on Document Analysis and Recognition. pp. 55- 61 ,(2012) , 10.1145/2432553.2432564
Zhixin Shi, Srirangaraj Setlur, Venu Govindaraju, Image Enhancement for Degraded Binary Document Images international conference on document analysis and recognition. pp. 895- 899 ,(2011) , 10.1109/ICDAR.2011.305
Anurag Singh Tomar, Gaurav Kumar Tak, Web Based Applications and Their Testing Approach International Journal of Innovative Research in Computer and Communication Engineering. ,vol. 2, pp. 4012- 4016 ,(2014)
Nija Babu, Preethi N.G., S.S. Shylaja, Degraded Document Image Enhancement Using Hybrid Thresholding and Mathematical Morphology indian conference on computer vision, graphics and image processing. pp. 701- 705 ,(2008) , 10.1109/ICVGIP.2008.55