A Novel Subpixel Circle Detection Method Based on the Blurred Edge Model

Author(s):  
Weihua Liu ◽  
Xianqiang Yang ◽  
Hao Sun ◽  
Xuebo Yang ◽  
Xinghu Yu ◽  
...  
2016 ◽  
Vol 54 ◽  
pp. 218-228 ◽  
Author(s):  
Hanqing Zhang ◽  
Krister Wiklund ◽  
Magnus Andersson

2014 ◽  
Vol 926-930 ◽  
pp. 3038-3041
Author(s):  
Cheng Wang

In this paper, we introduce a new method for ellipse detection. For any object has closed curve in a digital image, it is easy to calculate the centroid of the object. We assume the object is an ellipse, and then by rotating, scaling this object, it can be transformed to a circle. So, ellipse detection problem becomes circle detection problem. Compared with other detection methods, our method only need process border points of the object, hence has higher detection speed.


2015 ◽  
Vol 15 (02) ◽  
pp. 1540004
Author(s):  
Fumiya Iwasaki ◽  
Hiroki Imamura

In this paper, we propose a robust recognition method for occlusion of mini tomatoes based on hue information and the curvature. This method is used for a managing system using robots for hydroponic that we have proposed. In this system, robots need to recognize mini tomatoes to manage farmlands. In a lot of cases, mini tomatoes are covered partially by leaves or other tomatoes. Thence, the system needs a mini tomato recognition method in the situations including occlusion. First, this method detects red areas using hue information from a source image. Second, the method detects contours from the areas by using contour tracking. Finally, the method judges whether contours are mini tomatoes or not by using the curvature. We compared our method with circle detection method using Hough transform. Experimental results showed that the recognition rate of our method was 78.8%. On the other hand, the recognition rate of the comparative method was 47.9%. Therefore, we consider that the proposed method is appropriate for mini tomato recognition in the situations including occlusion.


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