Digital Image Processing using MATLAB and STATISTICA

Emilia Dana Seleţchi 1, Octavian G. Duliu 1

1University of Bucharest, Faculty of Physics, Department of Atomic and Nuclear Physics, Bucharest, ROMANIA

E-mail: seletchi@gmail.com

Abstract By using MATLAB 7.0.1., in a wide range of applications including image processing and visualizing data we performed statistical function such as: mean median, range and standard deviation, displaying image histogram and plotting the profile of intensity values on an X-ray CT scan. The plot fits panel allowed us to visually explore multiple fits to the current histogram data. We have been also created 2-D Stem Plots, Bar Plots (Plotmatrix), Polar Plots, Contour Plot, Vector Fields Graphs(Feather Graph and Compass Graph) and 3-D Surface Plot. STATISTICA 7.0 has been used to generate Normal Probability Plots, Scatter Icon Plots, 3-D Sequential graphs (Surface Plot and Contour Plot) and to apply multiple exploratory techniques such as Cluster Analysis. Keywords: Stem Plot, Plotmatrix, Polar Plot, Feather Graph, Compass Graph, Normal Probability Plot, Scatter Icon Plot, Cluster Analysis

1. Introduction

MATLAB is a high-level technical language and interactive environment for data analysis and mathematical computing functions such as: signal processing, optimization, partial differential equation solving, etc. It provides interactive tools including: threshold, correlation, Fourier analysis, filtering, basic statistics, curve fitting,, matrix analysis, 2D and 3D plotting functions. The operations for image processing allowed us to perform noise reduction and image enhancement, image transforms, colormap manipulation, colorspace conversions, region-of interest processing, and geometric operation. The toolbox functions implemented in the open MATLAB language can be used to develop the customized algorithms. STATISTICA software provides advances linear/nonlinear models, multivariate exploratory techniques (Cluster and Canonical Analysis), Industrial Statistics and Six Sigma Methods. The digital images processing were performed on medicine studies. 2. MATLAB 7.0.1. Applications 2.1. Image Processing

An X-ray Computed Tmography (CT) image is composed of pixels, whose brightness correspondsto the absorbtion of X-rays in a thin rectangular slab of the cross-secton, which is called a ’’voxel’’ [1,2].

The Pixel Region tool provided by MATLAB 7.0.1. superimposes the pixel region rectangle over the image displayed in the Image Tool, defining the group of pixels that are displayed, in extreme close-up view, in the Pixel Region tool window. The Pixel Region tool shows the pixels at high magnification, overlaying each pixel with its numeric value. For RGB images, we find three numeric values, one for each band of the image. We can also determine the current position of the pixel region in the target image by using the pixel information given at the bottom of the tool. In this way we found the x- and y-coordinates of pixels in the target image coordinate system. The current position of the pixel region rectangle is also carried out by selecting the Copy Position option from the Pixel Region tool Edit menu (Fig.1.).

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Figure 3. – The Histogram showing the number of pixels distributed on X-ray CT image (y-axis) for each level (gray value) and the plot fits (significant digits: 2)

a) b)

Figure 4. - Line Plots of X-ray CT scan: (a) on ox axes, (b) on oy axes

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