ABSTRACT
PSNR is one of the most often and universally used
method for measuring quality of image. In this paper we propose a methodology
for assessment of coating condition of bridge images. The defect recognition
algorithm includes conversion of captured images into grey level; these grey
level images are grouped into defective & non defective group. Further that
is processed to plot correspondence map. The correspondence map is measure of
matching image. Straight line with 450 in correspondence map indicates no
defect in scene image. In contrast if correspondence map produces nonlinear image
it indicates defect (rust) in scene image. The nonlinear shape of grey level
distribution in correspondence map can be analyzed by calculating Eigen values.
Two similar images will produce smaller Eigen value (approximately zero),
whereas it will be distinctly large for dissimilar images. The PSNR determines
proportion of rust in scene image with relation to reference image.
PROJECT OUTPUT
Contact:
Mr. Roshan P. Helonde
Mobile / WhatsApp:+91-7276355704
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