Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Spatiotemporal Region Enhancement and Merging for Unsupervized Object Segmentation | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2009 Article ID 797052 13 pages doi 10.1155 2009 797052 Research Article Spatiotemporal Region Enhancement and Merging for Unsupervized Object Segmentation K. Ryan 1 A. Amer 1 and L. Gagnon2 1 Department of Electrical and Computer Engineering Concordia University Montreal QC Canada H3G 1M8 2R D Department Computer Research Institute of Montreal CRIM Montreal QC Canada H3A 1B9 Correspondence should be addressed to A. Amer amer@ece.concordia.ca Received 22 January 2009 Revised 29 April 2009 Accepted 25 May 2009 Recommended by Bulent Sankur This paper proposes an unsupervized offline video object segmentation method that introduces a number of improvements to existing work in the area. It consists of the following steps. The initial segmentation utilizes object color and motion variance to more accurately classify image pixels in the first frame. Histogram-based merging is then employed to reduce oversegmentation of the first frame. During object tracking segmentation quality measures based on object color and motion contrast are taken. These measures are then used to enhance video objects through selective pixel reclassification. After object enhancement cumulative histogram-based merging occlusion handling and island detection are used to help group regions into meaningful objects. Compared to two reference methods greater success and improved accuracy in segmenting video objects are first demonstrated by subjectively examining selected frames from a set of standard video sequences. Objective results are obtained through the use of a set of measures that aim at evaluating the accuracy of object boundaries and temporal stability through the use of color motion and histograms. Copyright 2009 K. Ryan et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the .
