CANNY EDGE DETECTION AND CONTRAST STRETCHING FOR FACIAL EXPRESSION DETECTION AND RECOGNITION USING MACHINE LEARNING

2021 ◽  
Vol 24 (1) ◽  
pp. 35-66
Author(s):  
Dinesh Kumar ` P ◽  
B. Rosiline Jeetha
2012 ◽  
Vol 220-223 ◽  
pp. 1279-1283 ◽  
Author(s):  
Li Hong Dong ◽  
Peng Bing Zhao

The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adaptive median filtering algorithm to calculate the thresholds of Canny algorithm according to the grayscale mean and variance mean. This algorithm can protect the image edge details better and can restrain the blurred image edge. Experimental results show that this algorithm has improved the edge extraction effect under the case of noise interference and improved the detection precision and accuracy of the coal-rock image effectively.


Optik ◽  
2014 ◽  
Vol 125 (15) ◽  
pp. 3946-3953 ◽  
Author(s):  
Fei Hao ◽  
Jinfei Shi ◽  
Zhisheng Zhang ◽  
Ruwen Chen ◽  
Songqing Zhu

2011 ◽  
Author(s):  
Andrew Z. Brethorst ◽  
Nehal Desai ◽  
Douglas P. Enright ◽  
Ronald Scrofano

Sign in / Sign up

Export Citation Format

Share Document