Home   >   CSC-OpenAccess Library   >    Manuscript Information
A Novel System to Monitor Illegal Sand Mining using Contour Mapping and Color based Image Segmentation
Akash Deep Singh, Abhishek Kumar Annamraju, Devprakash Harihar Satpathy, Adhesh Shrivastava
Pages - 175 - 191     |    Revised - 31-05-2015     |    Published - 30-06-2015
Volume - 9   Issue - 3    |    Publication Date - May / June 2015  Table of Contents
Illegal Sand Mining, Contour Detection, Hough Transform, Color based Segmentation.
Developing nations face the issue of illegal and excessive land mining which has adverse effects on the environment. A robust and cost effective system is presented in this paper to monitor the mining process. This system includes a novel vehicle detection approach for detecting vehicles from static images and calculating the amount of sand being carried to prevent the malpractices of sand smuggling. Different from traditional methods, which use machine learning to detect vehicles, this method introduces a new contour mapping model to find important “vehicle edges” for identifying vehicles The sand detection algorithm uses color based segmentation since sand can have various colors under different weather and lighting conditions The proposed new color segmentation model has excellent capabilities to identify sand pixels from background, even though the pixels are lighted under varying illuminations. The detected amount of sand is checked against the maximum set threshold value specific to the recognized vehicle. Experimental results show that the integration of Hough features and color based image segmentation is powerful. The average accuracy rate of the system is 94.9%.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
A. Bensrhair et al., “Stereo vision-based feature extraction for vehicle detection,” in Proc. IEEE Intelligent Vehicles Symp., Jun. 2002, vol. 2, pp. 465–470.
A. Broggi, P. Cerri, and P. C. Antonello, “Multi-resolution vehicle detection using artificial vision,” in Proc. IEEE Intelligent Vehicles Symp., Jun. 2004, pp. 310–314.
A. El Maadi and X. Maldague, “Outdoor infrared video surveillance: a novel dynamic technique for the subtraction of a changing background of IR images,” Infrared Physics & Technology, vol. 49, no. 3, pp. 261–265, 2007.
A. Kundu, J.-L. Chen, “Texture classification using QMF bank-based sub-band decomposition,” CVGIP, GMIP, v. 54, p. 369–384, Sept. 1992.
A. L. Ratan, W. E. L. Grimson, and W. M. Wells, “Object detection and localization by dynamic template warping,” International Journal of Computer Vision, vol. 36, no. 2, pp. 131–148, 2000.
C. Tzomakas and W. Seelen, “Vehicle detection in traffic scenes using shadow,” Tech. Rep. 98-06 Inst. fur neuroinformatik, Ruhtuniversitat, Germany, 1998.
D. Comaniciu, P. Meer, “Robust analysis of feature spaces: Color image segmentation,” CVPR, June 1997, p. 750–755.
Dorko, G.; Schmid, C., "Selection of scale-invariant parts for object class recognition," Proceedings. Ninth IEEE International Conference on Computer Vision, 2003., pp.634,639 vol.1, 13-16 Oct. 2003
Fuzzy models, “Fuzzy Rule-based Models”, USENET: http://www.csee.wvu.edu/classes/cpe521/presentations/Sugeno-TSKmodel.pdf, 1997. [April. 29, 2015].
H.P. Narkhede. (2013). “Review of Image Segmentation Techniques,” International Journal of Science and Modern Engineering (IJISME). [Online]. 1(8), pp. 54-61. Available: http://www.ijisme.org/attachments/File/v1i8/H0399071813.pdf, [April. 29, 2015].
Ian T. Young, Jan J. Gerbrands, Lucas J. Van Vliet. “Fundamentals of Image Processing,” USENET:http://www.researchgate.net/publication/2890160_Fundamentals_Of_Image_Proc essing,1998. [April. 29, 2015].
Irwin Sobel, “History and definition of the Sobel operator”, USENET: http://www.researchgate.net/profile/Irwin_Sobel/publication/210198558_A_3x3_isotropic_gr adient_operator_for_image_processing/links/0a85e52eeba907a814000000.pdf, 2004, [April. 29, 2015].
J. Wu, X. Zhang, and J. Zhou, “Vehicle detection in static road images with PCA and wavelet-based classifier,” in Proc. IEEE Intelligent Transportation Systems Conf., Oakland, CA, Aug. 25–29, 2001, pp. 740–744.
J.L Marroquin,F. Girosi,,”Some Extentions of the K-Means Algorithm For Image Segmentation and Pattern Classification”, Technical Report, MIT Artificial Intelligence Laborartory, 1993.
M. Bertozzi, A. Broggi, and S. Castelluccio, “A real-time oriented system for vehicle detection,” Journal of Systems Architecture, pp. 317–325, 1997.
M. Lindenbaum and M. Fischer and A. M. Bruckstein.(1994). “On Gabor Contribution to Image Enhancement”. Pattern Recognition, 27(1), pp. 1-8.
M. Naveen Saviour. (2012). “Environmental impact of soil and sand mining: A review,” International Journal of Science, Environment and Technology. [Online]. 1(3), pp. 125-134. Available: http://www.ijset.net/journal/27.pdf [April. 29, 2015].
M. Unser, “Texture classification and segmentation using wavelet frames,” IEEE Tr. IP, v. 4, p. 1549–1560, Nov. 1995.
M.Luo, Y.F.Ma, H.J. Zhang,”ASpecial Constrained K-Means approach to Image Segmentation”,proc. The 2003 Joint Conference of Fourth International Conference on Informations Communications and Signal Processing and the Fourth Pacific Rim Conference on Multimedia, Vol.2, pp.738-742, 2003.
M.M. Chang, M.I. Sezan, A.M. Tekalp, “Adaptive Bayesian segmentation of color images,” JEI, p. 404–414, Oct. 1994.
Ojos Negros Research Group. “Sand Mining Impacts” USENET: http://threeissues.sdsu.edu/three_issues_sandminingfacts01.html. [April. 29, 2015].
Richard O. Duda, Peter E. Hart. “Use of Hough Transformation to detect lines and curves in pictures”,USENET:http://www.cse.unr.edu/~bebis/CS474/Handouts/HoughTransformPaper. pdf, 1971. [April. 29, 2015].
S. Belongie, et al., “Color- and texture-based image segmentation using EM and its application to content based image retrieval,” ICCV, 1998, p. 675–682.
S. Dutta, B.B. Chaudhuri, “Homogeneous Region based Color Image Segmentation”, in Proc. World Congress on Engineering and Computer Science, Oct. 2002, Vol II
Shi Na, Guan Yong and Liu Xumin, “Research on k-means Clustering Algorithm: An Improved k-means Clustering Algorithm,” in Third International Symposium on Intelligent Information Technology and Security Informatics, 2010, pp. 63-67.
Son, T.T.; Mita, S., "Car detection using multi-feature selection for varying poses," Intelligent Vehicles Symposium, 2009 IEEE, pp.507,512, 3-5 June 2009
T. Aizawa et al., “Road surface estimation against vehicles’ existence for stereo-based vehicle detection,” in Proc. IEEE 5th Int. Conf. Intelligent Transportation Systems, Sep. 2002, pp. 43–48.
T. Chang, C.-C.J. Kuo, “Texture analysis and classification with tree-structured wavelet transform,” IEEE Tr. IP, v. 2, p. 429–441, Oct. 1993.
T. Randen, J.H. Husoy, “Texture segmentation using filters with optimized energy separation,” IEEE Tr. IP, v. 8, p. 571– 582, Apr. 1999.
T.N. Pappas, “An adaptive clustering algorithm for image segmentation,” IEEE Tr. SP, v. 40, p. 901–914, Apr. 1992.
W.Y. Ma, Y.Deng, B.S. Manjunath, “Tools for texture/color based search of images,” Human Vision and Electronic Imaging II, Feb. 1997, Proc. SPIE, Vol. 3016, p. 496–507.
Y. Chen, X. Liu, and Q. Huang, “Real-time detection of rapid moving infrared target on variation background,” Infrared Physics & Technology, vol. 51, no. 3, pp. 146–151, 2008.).
Y. Deng, B.S. Manjunath, “Unsupervised segmentation of color-texture regions in images and video,” IEEE Tr. PAMI, v. 23, p. 800–810, Aug. 2001.
Z. Sun, G. Bebis, and R. Miller, “On-road vehicle detection using Gabor filters and support vector machines,” presented at the IEEE Int. Conf. Digital Signal Processing, Santorini, Greece, Jul. 2002.
Mr. Akash Deep Singh
Electronics and Instrumentation Engineering Department,Bits-Pilani KK Birla Goa Campus - India
Mr. Abhishek Kumar Annamraju
Electrical and Electronics Engineering Department,Bits-Pilani KK Birla Goa Campus - India
Mr. Devprakash Harihar Satpathy
Electronics and Instrumentation Engineering Department,Bits-Pilani KK Birla Goa Campus - India
Mr. Adhesh Shrivastava
Electrical and Electronics Engineering Department,Bits-Pilani KK Birla Goa Campus - India