This paper deals with image processing and feature extraction. Feature extraction plays a vital role in the field of image processing. There exist different image pre-processing approaches for feature extraction such as binarization, thresholding, resizing, normalisation so on...Then after these techniques are applied to obtain high clarity images. In Feature extraction object recognition and stereo matching are at the base of many computer vision problems. The descriptor generator module is changed for increasing the performance of algorithm. SIFT algorithm consist of two modules such as key point detection module and descriptor generation module. When compared to recent solution, the descriptor generation module speed is fifteen times faster and the time for feature extraction is also reduced.
Satellite images are unclear and it is very difficult to get information from them. This paper deals with the detection of edges of a satellite image. Here, edge detection is the fundamental tool of image segmentation. Image segmentation is a process of dividing an digital image into set of pixels, it is used to identify the objects and boundaries un an image.A set of connected pixels which forms boundary between two disjoint regions defines an edge,which is very important to acquire information from an image.There are many segmentation techniques like threshold, clustering, PDE, ANN based techniques, of all these methods edge based technique is the most optimum one. Canny edge detection algorithm is used to detect a wide range of edges in image uses multi-stage algorithm. Low error rate,good localization and single response are the main features of this algorithm.
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