Improved watershed segmentation for bucket object images of excavator robots
Wang Fu-bi · Chinese journal of construction machinery · 2013
During the implementation process of autonomous object excavation via excavator robots,the bucket object secures a critical position in vision information tracking.By employing the traditional threshold segmentation method,it is difficult to segment the bucket from the complicated environment.As such,the improved watershed segmentation method is proposed.Firstly,the bucket object images are processed using the fuzzy C-means clustering.Then,the gradient images are obtained from the initiallysegmented images.Next,the mark points are attained through comparing the gradient values and thresholding values.Finally,the mark points are used as the minimum points for watershed segmentation.Therein,its is found from experimental results that the segmentation effect is improved.