Earticle

초록

영어

Natural scene images are more susceptible to skew deformation as compared to document text which makes skew correction an indispensable step in scene text extraction. This work evaluates Murthy’s Devanagari scene word slant correction method [Signal, Image and Video Processing, 7(6), 2012] on Gurmukhi scene images. The method makes use of headline feature of Devanagari which also exist in Gurmukhi script. The headline of Gurmukhi word is found by perceiving farthest located salient points as its end-points and skew angle of headline is calculated from its slope. Gurmukhi word image is de-skewed using skew angle of identified headline. The method has been tested on 100 self-captured good quality Gurmukhi and 117 publically available Devanagari scene words with average accuracy of 62.8% and 72.2% respectively. The method has been found to be working well on few samples of defective scene words, provided actual end-points of headline are preserved. It has been observed that Murthy’s method is very simple to implement, does not require any pre-processing and give good results in wide variety of practical situations. However, this method does not work well for single character words with vowel above headline and words with identified headline parallel to horizontal axis.

목차

Abstract
 1. Introduction
 2. Dataset Collection
  2.1. Overview of Gurmukhi Script
  2.2. Natural Scene Words Dataset
 3. Methodology
 4. Results and Discussion
 5. Conclusion
 Acknowledgment
 References

키워드

저자

• Balwinder Singh [ Assistant Professor (Computer Science),Yadavindra College of Engineering, Punjabi University, Guru Kashi Campus,Talwandi Sabo, Punjab (India) ] Corresponding author
• Raman Maini [ Professor, Department of Computer Engineering, Punjabi University,Patiala,Punjab (India) ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605