AUTOMATIC IDENTIFICATION METHOD OF BLURRED IMAGES
Mikolaj Karpinski
mkarpinski@ath.bielsko.plUniversity in Bielsko-Biała, Department of Computer Science, Bielsko-Biała, Poland (Poland)
Nazarii Piontko
Ternopil Ivan Pul’uj National Technical University, Cathedra of Computer Science, Ternopil, Ukraine (Ukraine)
Volodymyr Karpinskyi
3D Scanners UK Ltd, the TechnoCentre, Coventry, United Kingdom (United Kingdom)
Abstract
Automatic identification method of the blur type is an important stage in automatic restoring and segmentation of partially blurred images.
This article describes automatic identification method of blurred images that also allows to estimate the blur angle parameter. This method contains five steps: 1) applying modified Sobel operator to the input image; 2) image cutting on perimeter in order to eliminate the negative effects occurred at the previous step; 3) construction sequentially blurred image’s versions from the step 2 with fixed radius; 4) similarity measure calculation of sequentially blurred image’s versions along with original image; 5) estimation of the criterion value. Method has been tested and has shown correct result in more than 90% of input images, and the average angle’s error does not exceed more than 8 degrees.
Keywords:
motion blur, image blurring, automatic identificationReferences
Aizenberg I., Butakoff C., Merzlyakov N.: Blurred image restoration using the type of blur and blur parameter identification on the neural network. Proc. SPIE 4667, Image Processing: Algorithms and Systems, 460 (May 23, 2002), 2002. 441-455.
Google Scholar
Dai S.: Motion from blur. CVPR, 2008.
Google Scholar
Krahmer F., Lin Y., Krahmer F.: Blind Image Deconvolution: Motion Blur Estimation. Mathematical Modeling in Industry X Workshop, Institute for Mathematics and Its Applications, 2006. 1-14.
Google Scholar
Liu R., Li Z., Jia J.: Image Partial Blur Detection and Classification. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
Google Scholar
Piontko N., Karpinski M.: Method of automatic identification of motion blurred images: Patent 82878: IPC G06K 9/00 G06K 9/46; Piontko N.V., Karpinski M.P.; Assignee: Temopil National Ivan Puluj Technical University (Ukraine), University of Bielsko-Biała (Poland). No u 2012 11096, filed 24.09.12; publ. 27.08.2013, Bulletin No 16 (in Ukrainian).
Google Scholar
Su B.: Blurred Image Region Detection and Classification. ACM Multimedia, 2011, 1397-1400.
Google Scholar
Tong H., Li M.: Blur Detection for Digital Images Using Wavelet Transform. Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference, Volume 1, 2004. 17-20.
Google Scholar
Authors
Mikolaj Karpinskimkarpinski@ath.bielsko.pl
University in Bielsko-Biała, Department of Computer Science, Bielsko-Biała, Poland Poland
Authors
Nazarii PiontkoTernopil Ivan Pul’uj National Technical University, Cathedra of Computer Science, Ternopil, Ukraine Ukraine
Authors
Volodymyr Karpinskyi3D Scanners UK Ltd, the TechnoCentre, Coventry, United Kingdom United Kingdom
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