A Novel Block Based Triangulation method to improve Video Stabilization

In Videos the motion based estimation technique the main factor and more complex process is the feature extraction. This is done by comparing the features in the adjacent frames in order to find the similarity Depending on the area of the image the complexity increases and the key feature extraction is complex and time consuming. The complexity of key point extraction is proportional to the area of the images (frames). This paper, we develop an block based feature extraction technique. Reducing the key features will reduce the accuracy of the image. Similarity is measured by analyzing the all edges of the image (frame with adjacent frame). The main challenge is the moving object while extracting features. This can be overcome by inter block feature matching. The local motion objects can be minimized by selecting three point in each image and its adjacent image. Mismatch is always inevitable in motion estimation no matter how powerful the feature point locator is. To get rid of this challenges, we propose a novel idea of forming a triangle based on three best features. The pixel values of the triangle formed in two images is accumulated and matched. It will guarantees the removal of faulty features. This will suit for only clear images not for images with defects like blur or shakes or overlapped or collapsed ones. we have best matched features, using that we calculate the global motion vectors. Videos are stabilized with the smoothened image which is done with the available filter in order to remove interferences and noise.