Object Identification For Computer Vision using Image Segmentation
Object detection for computer vision is one of the key factors for scene understanding. It is still a challenge today to accurately determine an object from a background where similar shaped objects are present in a large number. In this paper we proposed a method for object detection from such chaotic background by using image segmentation and graph partitioning. We build a feature set from the original object and then we train the system using the feature set and graph partitioning on the chaotic image. Testing is done on computer manipulated images and real world images. In both the cases our system identified the search object among other similar objects successfully.
Computer vision Image processing Image segmentation Graph partitioning
Debalina Barik Manik Mondal
Computer Science Department Bengal Institute of Technology Kolkata, India
国际会议
上海
英文
170-172
2010-06-22（万方平台首次上网日期，不代表论文的发表时间）