A systematic study on importance of image processing and its applications to the field of computer vision is carried out in this paper. An image is defined as an array, or a matrix, of square pixels (elements of picture) arranged in rows and columns. Image processing is a procedure of converting an image into digital form and carry out some operation on it, in order to get an improved image and take out several helpful information from it. Mathematically image processing is defined as the processing of a two dimensional picture by a computer i.e., an image is defined as a function of two real variables, like t(x, y) with an amplitude such as brightness of an image at the coordinate point (a, b). The outcome of image processing can be an image or a set of features or characteristics related to the image. Most image processing methods treats an image as a two-dimensional signal and implementing standard signalprocessing techniques to it. The goal of this operation can be divided into 3 categories. Firstly image processing in which input is an image and output is also an image; secondly image analysis in which input is an image and output are the dimensions or measurements. Finally image understanding in which input is an image and output is the standard description of an image. Some of the important applications of image processing in the field of science and technology include computer vision, remote sensing, feature extraction, face detection, forecasting, optical character recognition, fingerprint detection, optical sorting, argument reality, microscope imaging, lane departure caution system, Non-photorealistic representation, medical image processing, and morphological imaging.
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