Improved fuzzy-c means, Deep Belief Networks, and Morphological Operations in Object segmentation

摘要

The Object Detection is a very important application of Image Processing. Object detection has been one of the hottest issues in the field of Remote Sensing Image analysis. In this letter, inefficient Object Detection framework is proposed, which combines the strength of the unsupervised feature learning of Deep Belief Networks (DBNs) and Visual Saliency. This paper represents the research work is to propose an efficient object detection using the Fuzzy-c-means (MRF) and Deep Belief Networks based Image Segmentation. This research work is to increase the accuracy of the Object Detection. In, this it also integrate Fuzzy-c-means, Deep Belief Networks, and Morphological Operations in order to improve the Object segmentation rate.