In this paper, we propose an improved active shape model (ASM) which is based on a distance constraint to segment hearts from digital chest X-ray images. It includes three steps: 1) predict a rough position of a heart (RPOH) through projection, 2) train the shape model of the heart and register it to RPOH, so as to obtain an initial heart contour, and 3) utilize a cost function based on the distance constraint we introduce to get a more accurate contour of the heart. Further, to improve the accuracy of segmentation results, we minimize the cost function by minimizing the distance constraint. With the improved cost function, the probability of mark points falling into the non-target region can be reduced, thus improving the accuracy. The experiment results show that the improved cost function with eight neighboring points distance constraint effectively reduces influence of noises and avoids the problem of over segmentation of a heart to a certain extent.
The automatic recognition algorithm of lunar terrain is one of the hot topics in recent years. The algorithm which single use CCD or DEM data as data source can’t get a satisfactory result. Some algorithms combine CCD and DEM data sources and make terrain identification in time domain. The recognition rate of these algorithms is improved, but the time efficiency is not satisfactory. In order to solve the above problems, a fast terrain recognition algorithm based on wavelet domain be proposed. in this paper.