Shamik Tiwari; Vidya Prasad Shukla; Sangappa Biradar; Ajay Singh

Texture Features based Blur Classification in Barcode Images

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Author(s)

Shamik Tiwari ^1,* Vidya Prasad Shukla ¹ Sangappa Biradar ¹ Ajay Singh ¹

1. Faculty of Engineering & Technology, Mody Institute of Technology & Science

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2013.05.05

Received: 14 Jul. 2013 / Revised: 26 Aug. 2013 / Accepted: 15 Sep. 2013 / Published: 8 Nov. 2013

Index Terms

Blur, Motion, Defocus, Texture feature, Neural Network, Pattern Classification

Abstract

Blur is an undesirable phenomenon which appears as image degradation. Blur classification is extremely desirable before application of any blur parameters estimation approach in case of blind restoration of barcode image. A novel approach to classify blur in motion, defocus, and co-existence of both blur categories is presented in this paper. The key idea involves statistical features extraction of blur pattern in frequency domain and designing of blur classification system with feed forward neural network.

Cite This Paper

Shamik Tiwari, Vidya Prasad Shukla, Sangappa Biradar, Ajay Singh, "Texture Features based Blur Classification in Barcode Images", International Journal of Information Engineering and Electronic Business(IJIEEB), vol.5, no.5, pp.34-41, 2013. DOI:10.5815/ijieeb.2013.05.05

Reference

[1]J. Vartiainen, T. Kallonen, and J. Ikonen, “Barcodes and Mobile Phones as Part of Logistic Chain in Construction Industry,” The 16th International Conference on Software, Telecommunication, and Computer Networks, pp. 305 – 308, September 25-27, 2008.

[2]K. Q. Wang, “Barcode character segmentation for mobile cameras”, technical report of NOKIA, 2003.

[3]Jain A.K., “Fundamentals of Digital Image Processing”, Prentice Hall International, 1989.

[4]Gonzalez R.C., Woods R.E., “Digital Image Processing”, Prentice Hall, 2007.

[5]Tong, H., Li, M., Zhang, H., Zhang, C., “Blur detection for digital images using wavelet transform,” in proceedings of IEEE international conference on Multimedia and Expo, Vol. 1, pp. 17-20, 2004.

[6]Kai-Chieh Yang, Clark C. Guest and Pankaj Das, "Motion blur detecting by support vector machine", Proc. SPIE 5916, 59160R 2005.

[7]I.Aizenberg, N. Aizenberg, T. Bregin, C. Butakov, E. Farberov, N. Merzlyakov, O. Milukova “Blur Recognition on the Neural Network based on Multi-Valued Neurons”, Journal of Image and Graphics. Vol.5, 2000.

[8]Bolan Su, Shijian Lu, and Chew Lim Tan.,” Blurred image region detection and classification”, In Proceedings of the 19th ACM international conference on Multimedia (MM '11). ACM, New York, 2011.

[9]Renting Liu; Zhaorong Li; Jiaya Jia, "Image partial blur detection and classification," IEEE Conference on Computer Vision and Pattern Recognition, 2008(CVPR 2008), vol., no., pp.1, 8, 23-28 June 2008.

[10]Papageorgiou C. P. and T. Poggio, “A Trainable System for Object Detection,” Int. Journal of Comp.Vision, 38(1), pp. 15-33, 2000.

[11]Zhang J. and M. Marszalek, “Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study,” Int. Journal of Comp. Vision, Springer Science + Business Media, 10, pp. 1-26, 2006.

[12]Arivazhagan S et al., “Texture Classification using Ridgelet Transform,” Proc. of Sixth Intl. Conf. on Comp. Intell. and Multimedia Applications, pp. 2005.

[13]Arivazhagan S et al., “Texture Classification using Curvelet Statistical and Co-occurrence Features,” Proc. of 18th Intl. Conf. on Pattern Recognition, 2006.

[14]Devendran V et. al., “Texture based Scene Categorization using Artificial Neural Networks and Support Vector Machines: A Comparative Study,” ICGST-GVIP, Vol. 8, Issue IV, pp. 45-52, December 2008.

[15]Shamik Tiwari, Ajay Kumar Singh and V P Shukla, “Statistical Moments based Noise Classification using Feed Forward Back Propagation Neural Network”, International Journal of Computer Applications 18(2):36-40, March 2011.

[16]Shamik Tiwari, Ajay Kumar Singh and V P Shukla, Certain Investigations on Motion Blur Detection and Estimation, in Proceedings of International Conference on Signal, Image and Video Processing, IIT Patna, pp. 108-114 ,Jan,2012.

[17]Mohsen Ebrahimi Moghaddam, Mansour Jamzad,"Linear Motion Blur Parameter Estimation in Noisy Images Using Fuzzy Sets and Power Spectrum Images", EURASIP Journal on Advances in Signal Processing, Vol. 2007,pp. 1-9, 2007.

[18]Michal Dobe?, Libor Machala, Tomá? Fürst, “Blurred image restoration: A Fast Method of Finding the Motion Length and Angle”, Digital Signal Processing, Vol. 20, Issue 6, pp. 1677-1686, ISSN 1051-2004, December 2010.

[19]Su Bolan, S Lu.,C. L. Tan, “Restoration of Motion Blurred Document Images”, 27th ACM Symposium on Applied Computing, Italy, March 2012.

[20]Moghaddam, M.E., “A Mathematical Model to Estimate Out of Focus Blur,” in proceedings of 5th IEEE international symposium on Image and Signal Processing and Analysis, pp. 278-281, 2007.

[21]Sakano, M., Suetake, N., Uchino, E., “A robust Point Spread Function estimation for Out-of-Focus Blurred and Noisy Images based on a distribution of Gradient vectors on the polar plane,” in the Journal of Optical Society of Japan, co-published with Springer-Verlag GmbH, Vol. 14, No. 5, pp. 297-303, 2007.

[22]Tsung-Ying Sun, Sin-Jhe Ciou; Chan-Cheng Liu; Chih-Li Huo; "Out-of-focus blur estimation for blind image deconvolution: Using particle swarm optimization" , in proceedings of IEEE International Conference on Systems, Man and Cybernetics, pp.1627-1632, 2009.

[23]J Sklansky, image segmentation and feature extraction, IEEE transaction on systems, Man and Cybernetics, 8(4):237-247, 1978.

[24]A.Rosenfeld, Editor, Digital Picture Analysis, Springer Verlag, Berlin, 1976.

[25]C. Viard Gaudin, N. Normand, and D. Barba, “A bar code location algorithm using a two-dimensional approach,” in Proc. IEEE ICDAR’93, pp. 45– 48, Oct. 1993.

[26]S.J. Liu, H.Y. Liao, L.H. Chen, H.R. Tyan, and J. W. Hsieh, “Camera-based bar code recognition system using neural net,” in Proc. IEEE IJCNN’93, vol. 2, Nagoya, pp. 1301–1305, Oct. 1993.

[27]R. Howlett, S. Berthier, and G. Awcock, “Determining the location of industrial bar-codes using neural networks,” in Proc. IEEE IPA’97, vol. 2, pp. 511–515, July 1997.

[28]S. Arnould, G. Awcock, and R. Thomas, “Remote barcode localisation using mathematical morphology,” in Proc. IEEE IPA’93, vol. 2, pp. 642–646, July 1999.

[29]D. Chai and F. Hock, “Locating and decoding EAN-13 barcodes from images captured by digital cameras,” in Proc. IEEE ICICS’05, pp. 1556–1560, Dec. 2005.

[30]A. K. Jain and Y. Chen, “Bar code localization using texture analysis,” in Proc. IEEE ICDAR’93, pp. 41–44, Oct. 1993.

[31]R. Oktem, “Bar code localization in wavelet domain by using binary morphology” ,in Proc. IEEE SIU’04, pp. 499–501, Apr. 2004.

[32]Tropf, Alexander, and Douglas Chai. "Locating 1-D Bar Codes in DCT-Domain”, ICASSP2, pp. 741-44, 2006.

[33]Wenshuo Gao, Lei Yang, Xiaoguang Zhang, Huizhong Liu, “An Improved Sobel Edge Detection”, 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), Vol-5, pp.67 – 71, 2010.

[34]S. Wachenfeld, S. Terlunen, X. Jiang: http://cvpr.uni-muenster.de/research/barcode.

International Journal of Information Engineering and Electronic Business (IJIEEB)