An accurate and low complexity approach of detecting circular shape objects in still color images

Object detection is a critical step of many image recognition systems. In this paper, we discussed the circular shape object detection problem in still color images. The proposed method has an important feature of integrating color image edge extraction result with a novel circle parameter determination algorithm efficiently. First, an accurate isotropic edge detector is introduced to extract color image edge and calculate precise gradient direction of each potential edge pixel, which assures the high accuracy of subsequent circle detection. Then the detected potential edge results are verified by integrating them with spatial information and the result of region based analysis. Second we utilize just only one 2-dimensional accumulator array and one 1-dimensional accumulator array, which greatly reduce storage requirement and time complexity, to detect circles of any radius. Furthermore, the validity of detected potential circle centers is checked to avoid detecting false circles. Experimental results show that our method is robust and effective in locating objects with complete or incomplete or concentric circle boundary in real color images without any prior knowledge.