Blurred Image Recognition by Legendre ’ s Moment Invariants

Introduction An image may be defined as two dimensional function f(x, y), x and y are spatial coordinates. Digital image processing refers to processing of digital images using digital computers and the digital are represents by picture elements or pixels. Computing the average intensity of an image would not considered an image processing operation. They are three types of processes 1. Low level processes 2. High level processes 3. Mid-level processes In the low level process , input and output are represented by images, the mid-level process are characterized by the factor , input are images and the output are attributes extracted from images , and the high level is represented by image analysis. Image in the form of slide, photograph is first digitized and stored as a matrix of binary digits in computer memory. The digitized images are processed and or displayed on a high resolution monitor. For display , image is stored in rapid accessThe widely accepted standard linear model describes the imaging process by a convolution of an unknown original image f(x,y) with a space invariant point spread function (PSF) h(x,y)which refreshes the monitor at 30 frames/s for continuous display. One of the frequent tasks in image processing is the recognition of an image (or , more frequently, of an object on the image) against images stored in a database. Whereas the images in the database are supposed to be ideal, the acquired image represents the scene mostly in an unsatisfactory manner. Because real imaging systems as well as imaging conditions are imperfect, an observer image represents only a degraded version of the original scene. Blur is introduced into the captured image during the imaging process by such factors as diffraction, lens aberration, wrong focusing, and atmospheric turbulence. Image processing is a very active area that has impacts in many domains from remote sensing, robotics, traffic surveillance, to medicine. Image recognition methods are mainly applicable in automatic target recognition and tracking, character recognition, 3-D scene analysis and reconstruction. The image is captured through the camera , if that image is in unsatisfactory manner means that image represents the blurred image. The images are affected because of the following factors , they are, 1. Wrong focusing 2. Atmospheric turbulence 3. Lens aberration 4. Out of focus Some kind of noises ( e.g Gaussian noise, Salt & pepper noise, additive noise with different standard deviations). g(x,y) = (f * h) (x,y) where, g(x,y) represents the observed image h(x,y) describes the imaging system it is supposed to be unknown Image processing Toolbox MATLAB is a high performance language for technical computing. It integrates computation, visualization, and programming in an easy to use environment where problems and solutions are expressed in familiar mathematical notation. The name MATLAB stands for Matrix Laboratory. MATLAB was originally written to provide easy access to matrix software developed. The toolbox supports a wide range of image processing operations, including Spatial image transformation, Morphological operations, Transforms, Image analysis and enhancement, image restore, Deblurring Literature review Existing system Since the recent advances in electrical devices enable widespread uses of mobile cameras, degradation of the image caused by camera motion has been considered a key issue. However, most conventional research has not been able to guarantee satisfactory quality of the resultant image because of the ill-posed characteristic of the image restoration model. In classical image deblurring approaches, a point spreadfunction (PSF) is assumed to be known. Based on the known PSF, image deconvolution has been applied to restore images. In real applications, however, the PSF is scarcely known. Therefore, the PSF is estimated in the space domain or frequency domain.