Infrared image edge recognition and defect quantitative determination based on the algorithm of fuzzy C-means clustering and Canny operator

Tang Qingju; Liu Junyan; Wang Yang; Liu Yuanlin; Mei Chen

doi:10.3788/irla201645.0928001

[1] Sneha Arora, Sanyam Anand. A new approach for image steganography using edge detection method[J]. International Journal of Innovative Research in Computer and Communica-tion Engineering, 2013, 1(3): 626-629.

[2] Rashmi, Mukesh Kumar, Rohini Saxena. Algorithm and technique on various edge detection: a survey[J]. Signal & Image Processing, 2013, 4(3): 65-75.

[3] Jamal Raiyn. A novel automatic object detection in images[J]. Current Research in Computer Science, 2013, 1(1): 1-4.

[4] Szilagri L, Szilagri S, Benyo B. Efficent inhomogeneity compensation using Fuzzy C-means clustering modles [J].Computer Methods and Programs in Biomedicine, 2012, 1(1): 1-4.

[5] Fagbola T Mathew, Babatunde R Seyi. Image clustering using a hybrid GA-FCM algorithm[J]. International Journal of Engineering and Technology, 2013, 3(2): 99-107.

[6] Mohamed Mahjoub A. Improved FCM algorithm applied to color image segmentation[J]. Canadian Journal on Image Processing and Computer Vision, 2011, 2(2): 16-19.

[7] Cao Junfeng, Shi Jiacheng, Luo Haibo, et al. Image enhancement using clustering and histogram equalization [J]. Infrared and Laser Engineering, 2012, 41(12): 3437-3441. (in Chinese)

[8] Li Qinghui, Li Aihua, Su Yanzhao, et al. Fire detection algorithm using FCM clustering[J]. Infrared and Laser Engineering, 2014, 43(5): 1661-1665. (in Chinese)