Title :
Objective Distortion Measure for Binary Text Image Based on Edge Line Segment Similarity
Author :
Cheng, Jun ; Kot, Alex C.
Author_Institution :
Workstation Resource Lab., Nanyang Technol. Univ., Singapore
fDate :
6/1/2007 12:00:00 AM
Abstract :
This paper proposes a new approach to measure the distortion introduced by changing individual edge pixels in binary text images. The approach considers not only how many pixels are changed but also where the pixels are changed and how the flipping affects the overall shape formed by the edge line. Similarities between the edge line segments in the original and distorted image are compared to measure the distortion. Subjective testing shows that the new distortion measure correlates well with human visual perception
Keywords :
distortion; document image processing; image resolution; image segmentation; binary text image; edge line segment similarity; edge pixels; flipping; objective distortion measure; Data encapsulation; Distortion measurement; Humans; Image processing; Image segmentation; PSNR; Pixel; Shape; Testing; Visual perception; Binary text image; distortion measure; Algorithms; Artifacts; Artificial Intelligence; Computer Graphics; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Printing; Signal Processing, Computer-Assisted; Subtraction Technique;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2007.896619