DocumentCode :
682757
Title :
Application of improved wavelet threshold de-noising algorithm in work piece inspection
Author :
Dan Li ; Xin Zhang ; Ting Jiang ; Meng Zhang
Author_Institution :
Sch. of Electr. & Inf. Eng., Anhui Univ. of Technol., Ma´anshan, China
Volume :
01
fYear :
2013
fDate :
16-18 Dec. 2013
Firstpage :
256
Lastpage :
260
Abstract :
Image de-noising is an important step to improve the AOI (automated optical inspection) image quality of automobile work piece. After analyzing the theory of wavelet transform and the characteristics of traditional soft and hard wavelet threshold de-noising methods, an improved threshold de-noising method was proposed. The new method overcomes the discontinuous in hard threshold de-noising method and reduces the permanent bias in soft threshold de-noising method. At last hard threshold de-noising, soft threshold de-noising method and improved threshold de-noising are used to reduce noises in the same image of workpiece. The results show that the improved threshold method is superior to the traditional soft and hard wavelet threshold de-noising methods in decreasing RMSE and improving PSNR.
Keywords :
automatic optical inspection; automobile industry; automotive components; image denoising; production engineering computing; wavelet transforms; AOI image quality; PSNR; RMSE; automated optical inspection; automobile work piece; hard threshold denoising method; image denoising; improved wavelet threshold denoising algorithm; noise reduction; permanent bias; soft threshold denoising method; wavelet transform; work piece inspection; workpiece image; Image denoising; Noise; Noise reduction; Wavelet coefficients; Wavelet domain; Automated optical inspection; Image de-noising; Wavelet transform; Workpiece;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-2763-0
Type :
conf
DOI :
10.1109/CISP.2013.6743997
Filename :
6743997
Link To Document :
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