| 摘要 |
Object detection and tracking operations on images that may be performed independently are presented. A detection module receives images, extracts edges in horizontal and vertical directions, and generates an edge map where object-regions are ranked by their immediacy. Filters remove attached edges and ensure regions have proper proportions/size. The regions are tested using a geometric constraint to ensure proper shape, and are fit with best-fit rectangles, which are merged or deleted depending on their relationships. Remaining rectangles are objects. A tracking module receives images in which objects are detected and uses Euclidean distance/edge density criterion to match objects. If objects are matched, clustering determines whether the object is new; if not, a sum-of-squared-difference in intensity test locates matching objects. If this succeeds, clustering is performed and rectangles are applied to regions and merged or deleted depending on their relationships and are considered objects; if not the regions are rejected.
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