Inshore ship and hybrid object detection and recognition using context-aware color and shape model

The oceanography is the technnique of analyzing the oceanic imagery in order to find the useful information about ships, objects. The technique is helpful in detecting the lost ships, boats, aero planes, debris, containers, etc. It may consists of the large volumes of image data, which must be further shortened to find the useful information to find the lost objects in the oceanic area. In this simulation study, the proposed model has been annalysd to detect the objects in the oceanic images in order to minimize the human effort to shortlist the images containing the useful information. The simulative analysis has been designed to use the combination of the color and shape based analysis to detect the objects accurately. The three dimensional color pixel (24-bit pixel) based approach has been used along with the shape and size evaluation to achieve the higher accuracy for the target objects. The MATLAB based simulation is performed on various kinds of satellite images, and the evaluation has been performed on the basis of various performance parameters. The results have shown the effectiveness of the proposed model.