15-06-2013, 02:39 PM
NEW IMAGE PROCESSING TOOLBOX USING MATLAB CODES
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ABSTRACT
The idea is designing and programming a new image processing toolbox using Matlab codes. This toolbox is used as an education tools to process digital images and help the students to understand how are the different image processing functions work?; such as how the image for any format and size is opened?, how are the slice images combining to get a movie image as a video camera did?, displaying the original images and their results after processing in the same window for compression purposes , show image histogram, running watershed segmentation method, enhancing, threshoding ,separate color image into its components , adding Gaussian and salt and fever noises to the image then doing successive filtering process , and plotting any signal data profile. Also in our package, it is easy to connect with all Matlab functions and using all Matlab dialog boxes designs. Finally all the functions in this toolbox are collected and programmed using Matlab codes as we see through the text of this paper. The toolbox is easy to use in image processing field.
INTRODUCTION
An image may be defined as a two –dimensional function, f(x, y), where x and y are spatial (plane) coordinates, and the amplitude of f at any pair coordinates (x, y) is called the intensity or gray level of the image at that point. When x, y , and the amplitude values of f are all finite, discrete quantities, we call the image a digital image. So; a digital image is a two-dimensional array of small square regions known as pixels. [1][2]
What Is the Image Processing Toolbox?. The Image Processing Toolbox is a collection of functions that extend the capability of the MATLAB® numeric computing environment. The toolbox supports a wide range of image processing operations, including: open image file, add noise of a given type (e.g salt &pepper ,Guassian, Speckels...) to intensity image , 2-D median filtering and adaptive filtering, Image analysis and enhancement, Color Image decomposition into RGB Channels, Image histogram, Image segmentation, image Multithresholding,, image movie , signal plotting and others , see Fig(2). Many of the toolbox functions are MATLAB M-files, a series of MATLAB statements that implement specialized image processing algorithms.
IMAGE FORMATS
1-Bit-Map Monochrome Image: in a monochrome (black/white) image, (like the example Fig (1 a) ), each pixel is stored as a single 0 or 1 value (bit).
2-A grayscale image: (like the example Fig (1 b)), usually requires that each pixel be stored as a value between 0 - 255 (byte), where the value represents the shade of gray of the pixel. The number of gray levels typically is an integer power of 2 (L=2K). The image formats are .Gif, .tif, .Jpeg, and .bmp.3- We also used color images (RGB images) and separated into their components (Red, Green, and Blue).
INTENSITY HISTOGRAM
In an image processing context, the histogram of an image normally refers to a histogram of the pixel intensity values. This histogram is a graph showing the number of pixels in an image at each different intensity value found in that image. For an 8-bit grayscale image there are 256 different possible intensities, and so the histogram will graphically display 256 numbers showing the distribution of pixels amongst those grayscale values. See Fig (4) How It Works: The operation is very simple. The image is scanned in a single pass and a running count of the number of pixels found at each intensity value is kept. This is then used to construct a suitable histogram.
CONCLUSION
1- Through the main program of our toolbox, it is easy to open and process different image file formats for different sizes such as BMP, GIF, and JPEG Images.
2- The toolbox shows easily the program codes with comments to be understood.
3- It is easy to run the toolbox (including the whole view of the menu items, figures and functions). It easy to run any function separately and it is possible to modify any function.