Brick stack anomaly detection and recognition based on machine vision

Guangxue Xuebao/Acta Optica Sinica

Volumn 31, Issue 7, 2011, Pages

  Xiang, Shoubing ^a,b   Su, Guangda ^b   Chen, Jiansheng ^b   Liu, Jing ^b   Tan, Xiaohui ^a  

^a SICHUAN ENGINEERING TECHNICAL COLLEGE   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

Automatic brick stack system; Brick stack anomaly recognition; Image processing; Machine vision

Indexed keywords

ANOMALY DETECTION; AUTO-DETECTION; BRICK-STACK-ANOMALY RECOGNITION; CANNY EDGE DETECTORS; DETECTION ACCURACY; LABOR INTENSITY; MEDIAN FILTERING; MULTISCALES; ON-MACHINES; POLAR ANGLES; RECOGNITION METHODS; STACK SYSTEMS; VERTICAL EDGES;

COMPUTER VISION; DETECTORS; HOUGH TRANSFORMS;

BRICK;

EID: 79960877359     PISSN: 02532239     EISSN: None     Source Type: Journal    
DOI: 10.3788/AOS201131.0715002     Document Type: Article

References (23)

1. Wang Dongyun, Sun Yong. How to improve stacking process to improve product quality [J]. Brick and Tile, 2008, (4): 46-47.
2. Wang Haichen. The application of automatic stacking system in brickfield [J]. Brick and Tile, 2008, (9): 75-76.
3. Shi Hongwen. The development of brick and tile mechanical equipment in China [J]. Brick and Tile, 2011, (1): 29-30.
4. Luo Nan. Research on Environmental Impact of Sintered Brick Production in China [D]. Beijing: Beijing University of Technology, 2009.
5. Xiao Liang, Zhao Shiwu. The research of high-performance insulation block equipment [J]. Wau Reform and Building Energy Conservation, 2008, (1): 60-61.
6. J. G. Brankov, A. Saiz-Herranz, M. N. Wernick. Noise analysis for diffraction enhanced imaging [C]. Chicago: Biomedical Imaging, 2004, 2 (4): 1428-1431.
7. B. Jin, N. Park, K. M. George et al.. Modeling and analysis of soft test/repair for CCD based digital X-ray systems [J]. IEEE Trans. Instrumentation and Measurement, 2003, 52 (6): 1713-1721.
8. J. L. Mateo, A. Caballero Hernandez. Finding out general tendencies in speckle noise reduction in ultrasound images [J]. Expert Syst. Appl., 2009, 36 (4): 7786-7797.
9. Ouyang Chengsu, Huang Yongxuan. A new de-noising method for X-ray image using fuzzy weighted median filter [J]. Acta Photonica Sinica, 2010, 39 (8): 1372-1376.
10. Liu Songtao, Ma Linpo, Yin Fuliang. A color image vector median filtering algorithm based on noise estimation and double weighted spatial distance and magnitude value [J]. J. Optoelectronics·Laser, 2011, 22 (1): 131-135.
11. Wang Taiping, He Yuyao, Li Gang. Median filter with improved all direction windows for road detecting [J]. Computer Measurement & Control., 2008, 16 (2): 150-152.
12. Zhang Wenpan, Wu Junhui, Zhu Zhen et al.. Application of improved crossing based median filter in image processing of IR image [J]. Electronics Optics & Control., 2006, 13 (1): 83-86.
13. Zhang Xinming, Dang Liuqun, Xu Jiucheng. Fast adaptive image median filter based on crossing windows [J]. Computer Engineering and Applications, 2007, 43 (27): 37-39.
14. Lou Shuai, Ding Zhengliang, Yuan Fen. Iterative image restoration algorithm based on contourlet transform [J]. Acta Optica Sinica, 2009, 29 (10): 2768-2773.
15. Wu Xiaoyue, Guo Baolong, Tang Lu et al.. A new adaptive image denoising method based on the nonsubsampled contourlet transform algorithm [J]. Acta Optica Sinica, 2009, 29 (8): 2147-2152.
16. Jiang Guoquan, Ke Xing, Du Shangfeng et al.. Crop row detection based on machine vision [J]. Acta Optica Sinica, 2009, 29 (4): 1015-1020.
17. Ji Ying, Liu Gang, Shen Wei. A method based on machine vision to obtain a guidance directrix [J]. Acta Optica Sinica, 2009, 29 (12): 3362-3366.
18. Lü Qieni, Gao Yan, Ge Baozhen et al.. Digital holographic particle sizing with hough transform [J]. Chinese J. Lasers, 2009, 36 (4): 940-944.
19. Kang Wenjing, Ding Xuemei, Cui Jiwen et al.. Fast straight-line extraction algorithm based on improved Hough transform [J]. Opto-Electronic Engineering, 2007, 34 (3): 105-108.
20. Zhu Fangfagn, Gu Hongbin, Sun Jin. A line detection algorithm based on improved Hough transformation [J]. Computer Technology and Development, 2009, 19 (5): 20-22.
21. R. Deriche. Using Canny's criteria to derive a recursively implemented optimal edge detector [J]. Int. J. Comput. Vision, 1987, 1 (2): 167-187.
22. Building Materials Institute, Nanjing, Jiangsu. GB 5101-2003 Fired Common Bricks [S]. Beijing; Standard Press of China, 2004.
23. China National Building Materials Company. GB/T 2542-2003 Test Method for Wall Bricks [S]. Beijing: Standard Press of China, 2003.