Title :
Laminated paper counting algorithm based on compressive sensing and hough transform
Author :
Hui Wang ; Dongfang Chen ; Xiaofeng Wang
Author_Institution :
Hubei Province Key Lab. of Intell. Inf. Process., Wuhan Univ. of Sci. & Technol., Wuhan, China
Abstract :
According to the problem that conventional laminated paper counting algorithms have some unavoidable shortcomings such as high dependence on the quality of laminated paper and noise sensitivity, we propose a laminated paper counting algorithm based on compressive sensing (CS) and Hough transform (HT). In the proposed algorithm, the over-complete dictionary which is created by dispersing the Hough transform space of straight lines acts as the sparse matrix. Making use of high degree of sparse nature of the laminated paper image, we can obtain the accurate result through using CS theory. Experimental results on simulation images and laminated paper images have shown that our proposed algorithm can effectively restrain noise of the laminated paper image, and will get accurate experimental results with fewer CS measurements.
Keywords :
Hough transforms; compressed sensing; image processing; sparse matrices; CS theory; HT; Hough transform; compressive sensing; laminated paper counting algorithms; over-complete dictionary; sparse matrix; Image coding; Image reconstruction; Matching pursuit algorithms; Signal to noise ratio; Sparse matrices; Transforms; Hough transform; compressive sensing; laminated paper counting; over-complete dictionary;
Conference_Titel :
Information Technology and Electronic Commerce (ICITEC), 2014 2nd International Conference on
Print_ISBN :
978-1-4799-5298-4
DOI :
10.1109/ICITEC.2014.7105593