Filtering erroneous frame-by-frame results for planar rectangular objects localization in a video using matching transform graph
The detection of rectangular objects is an important part of document recognition and workflow automation. At the same time, outlier noise may appear during the detection process – falsely determined coordinates of the document location, negatively affecting the overall quality of object detection and further processing. The task of filtering such noise when detecting a flat rectangular object on frames of a video sequence by constructing a single coordinate system is posed. The proposed method is based on the coordination of the graph of estimated projective transformations of frames with templates and frames among themselves. In the experiments used, simulated outlier applied to some frames of the video sequence. To assess the quality of the algorithm, the results of object location before and after the module matching the graph with the true location of the object are compared. This assessment is based on the open MIDV-500 database of video filming of identity documents. This data set demonstrates a reduction in the cumulative error compared to the results before using graph matching in calculating projective transformations.