@article{(Open Science Index):https://publications.waset.org/pdf/9688,
	  title     = {A New Voting Approach to Texture Defect Detection Based on Multiresolutional Decomposition },
	  author    = {B. B. M. Moasheri and  S. Azadinia},
	  country	= {},
	  institution	= {},
	  abstract     = {Wavelets have provided the researchers with
significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional
by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to
detect the defect of texture images by using curvelet transform.
Simulation results of the proposed method on a set of standard
texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing
discontinuity in two-dimensional functions compared to wavelet
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {5},
	  number    = {1},
	  year      = {2011},
	  pages     = {119 - 123},
	  ee        = {https://publications.waset.org/pdf/9688},
	  url   	= {https://publications.waset.org/vol/49},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 49, 2011},