Oval detection in color images

The paper presents an oval detection algorithm in color images. First a SOBEL operator is used to do edge detection and enhancement. Then Nilsson´s algorithm for contour detection is applied with small changes. To enhance robustness against gaps in possible contours, adjacency range is increased. As a result, sets of potential contours are obtained. As an alternative the authors introduce their new approach which first identifies regions of potential ellipses, discarding all that do not fit the aspect ration threshold set up by the authors. Then each potential region is split in three segments. For each segment the mean gradient is calculated and a possible oval is identified if the mean gradient is increasing or decreasing from the first to the third region. Once a potential oval is identified, ten point couples with the largest distances are used to determine the major axis. The deflection angle for the minor axis is computed and two points are found nearest to that line so at the end the five points of a potential ellipse are found. Two indicators are now used to reflect similarity and approach to do best possible ellipse fitting.