A Robust Blob Detection and Delineation Method
Liang Wang, Hehua Ju · 2008
This work presents a robust method to detect blob and fit its contour in image. Previous methods for blob detection and delineation were either liable to fail with outliers and noise or computationally expensive. By incorporating the prior information of the region-of-interest and introducing the concept of the kernel MSER, the modified MSER detection method can detect the unique blob which is the most stable region to represent the blob. For further processing, the constrained least squares method by incorporating pruning technique is used to fit the ellipse corresponding to the contour of the detected blob. With this proposed method, we can detect and fit blob with high accuracy. The experiments show the validity of the proposed method.