Image Processing is the Process of Converting an Image into Digital Form

Digital Photography has become one of the most simplified and effective way of capturing and using the images. Digital images are very high in quality and also with the ease of viewing, editing and transferring it to any computers or mobile devices making it a very cost effective way of managing the images (Kornhaber, Betihavas, & Baber, 2015).

Pixel count - A pixel is a physical point in an image represented on the screen. The intensity of each pixel is variable. The more pixels, the better the quality. Resolution

The Role of Components within a given computer system in the Production and Manipulation of Graphics

Another step in pre-processing is to make the image width and height divisible by 8. Let w and h represent the width and height of the image respectively. w and h are converted into w* and h* such that 8|w* and 8|h* are as follows in (1) and (2):

1. Processing is changing or manipulating raw data within an IS to produce information (Sousa, 2015).

Image Analysis: An effective image employs specific techniques to relay its purpose. This image of 6 year old Alex Donley uses the following techniques to influence the reader or viewers perception of the chapter. Framing, layout, colour, symbols and focus are all crucial aspects of the image.

Digital Camera: Images play an important role in the graphic images. It is like if there are no images then there cannot be any graphics. So to edit any graphic image you will need to have an image and to get image you need to have a digital camera which will let you capture anything you want so you can use that image to edit. There are variety of cameras available in the market from very cheap to very expensive but both of them does the same work. However, the cheaper one will not have enough clearer picture or the resolution so you can choose to buy a camera with a good megapixel and resolution which will make your work easier as you will get good images.

In radiography, picture archiving and communication system enables the capture, storage, retrieval and sending of digital

The basic principle of this algorithm is to recognize the input paper currency. First of all acquired the image from a particular source. As in this thesis we use for reference images. System read the particular image. Then resize the image. After that the color separator convert the image into RGB to Gray scale and then in binary image. After that the system use color noise median filter. The currency length detector detects the length of the currency. Using the feature extraction techniques the system detect the particular feature of that currency and then the system use pattern matching algorithm to math that particular feature. The input image match with particular database image and according to that we find the currency. In this way this thesis design a automatic system in which we can recognized the paper currency.

Our bodies are an amazing machine that interpret the world we live in using different processing systems. The visual information process is a system used to perceive our environment and send this information to our brain, the processing center of the body. One of the most important and often the initial sense used in perceiving our environment is vision. Vision may be the leading prominent sense we use in perception.

• The signal-processing unit sends the information to the display, where it appears as various colors depending on the intensity of the infrared emission. The combination of all the impulses from all of the elements creates the image.

The outline of the stages of the image processing pipeline is; realign (affine), skull scripting, statistical edge detector (multi-scale, multi-modal), extract statistical features, use it to build SVM. The robustness of implementation will be tested with Pixel Correspondence Metric (PCM). The same pipeline will be followed for an unsupervised approach using leave one out (LOOCV). The filter size, parametric and non-parametric features like mean, variance, rank, U Mann Whitney test etc will be evaluated and an optimal performer will be selected.

In this report I will be discussing the different file formats, compression techniques, image resolution and colour depth. I will be explaining the different purposes, then, after I have issued an in-depth explanation of image quality and file size I will be completing a final conclusion about the best ones to use for certain tasks.

However as the authors stressed, probably more significant than the change in how images are produced, distributed and used, are the ideas to which the changes are giving rise and how digital imaging is challenging and changing traditional ways of seeing and thinking. It seems that our traditional belief that ‘the camera never lies’ has been brought into question. It also appears important to consider who

This is also as preparation of the next step where the histogram will be divided into two regions based on its average value. The stretched-histogram will provide a better pixel distribution of the image channels and thus gives a more accurate average value of the channel which represents the average value of the channel for the whole dynamic range. The equation (6) is used to stretch the histogram of respective color channel to the whole dynamic range. Pin and Pout are the input and output pixels, respectively, and imin, imax, omin, and omax are the minimum and maximum intensity level values for the input and output images,