Object Detection from the Satellite Images Using Divide and Conquer Model
Lakhwinder Kaur, Vinod Kumar Sharma
Object detection is the technique of detection of the object type is sub-type of automatic computer vision. This is a growing research area. Object detection in oceans is called oceanology or oceanological computer vision. In the oceans, the object detection is used to find the information about the ships, Islands and other objects. The ocean imaging is done by the satellites and falls under the SAR or aerial imaging category. In this paper, we are proposing a new method of object detection by using the shape and color analysis, followed by divide and conquer model. The proposed algorithm can be used to detect the crashed aeroplanes, floating containers and many other objects. The proposed system can be used to find any physical object whose colour pattern and shape can be specified (known). Proposed system will be produce accurate results than any existing object detection algorithm. Proposed algorithm will perform more in-depth analysis because it uses the combination three popular approaches: object based analysis, pixel based analysis and shape based analysis.
Keywords: object based analysis, pixel based analysis, shape analysis, ship detection, debris detection
Edition: Volume 3 Issue 9, September 2014
Pages: 1385 - 1387