scholarly journals Perancangan Aplikasi Pengolahan Citra Digital Untuk Menentukan Bibit Unggul Biji Kopi dengan Metode Canny Edge Detection

2020 ◽  
Vol 7 (3) ◽  
pp. 421
Author(s):  
Sandrak A Batubara

The image of coffee beans is very important to recognize, with the image of coffee beans will make coffee lovers easier to recognize the coffee beans just by looking at their image without having to locate where the coffee grows. Coffee is a beverage known in Indonesia, the detection of coffee beans is very important because the number of seeds that are similar to coffee beans, so the process of detecting coffee beans is very necessary so that coffee beans can be identified, with the method of cany can detect real coffee beans. The cany method is a method that can detect coffee beans by recognizing the coffee beans.

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

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