Image Processing
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Introduction
An Digital Image is Two dimensional structure composed of pixels (picture element) which can be thought of as small dots on the screen. Pixels are arranged in rows and columns which forms matrix. If an image is of size m-by-n if it is composed of m pixels in the vertical direction and n pixels in the horizontal direction.
This Digital image is Broadly classified into Binary, gray scale, color image. In case of binary image Each pixel is just black or white. Since there are only two possible values for each pixel, we only need one bit per pixel(0 or 1). In this case ‘0’ represents black and ‘1’ represents white. In Gray scale image Each pixel is a shade of grey, normally from (black) to (white). If an image is 8-bit each pixel can be represented by eight bits, or exactly one byte. It means pixel value ranging from 0 to 255. Generally they are a power of 2 i.e in this case 2^8. In case of color image (RGB) each pixel has a particular color; that colour being described by the amount of red, green and blue in it. If each of these components has a range 0-255, this gives a total 255x255x255=16,777,216 different possible colors in the image. This is enough colors for any image. Since the total number of bits required for each pixel is 24.
Digital Image processing involves changing the nature of an image in order to either
1. improve its pictorial information for human interpretation,
2. render it more suitable for autonomous machine perception.
Applications of digital image processing
Image processing has an enormous range of applications; almost every area of science and technology can make use of image processing methods. Here some of the application are indicated.
1.Medicine
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X-rays, MRI or CAT scans images can be inspected and analyzed
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Analysis and identification of Cancer tissue in the Human body.
2.Agriculture
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Satellite/Aerial views of land and inspection of crops.
3. Industry
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Automatic inspection of items on a production line,
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Inspection of paper samples.
4. Law enforcement
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Fingerprint and face analysis,
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sharpening or de-blurring of camera images.
Research Scope and Areas.
Digital image Stenography
Face recognition and detection
Finger print recognition and detection
Digital Image Enhancement
Digital Image compression
Medical image processing
3-Dimensional image processing
Digital Image Restoration
Digital image Fussion
Image segmentation
Digital Image watermarking
Digital
Analysis, Implementation and algorithm development Tools:
There are many commercial and open source tools available to process the Digital images. Some of such tools are Matlab, simulink, Sailab, Turbo C , Xilinx etc. All the tools has its own way of syntax, declaration, commands. Many user guide or manuals and books available to do development.
