Steven L. Eddins

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% hand optimized functions >> g_sobel_best=edge(f,’sobel’, 0.05); % figure 10.7(b) %0.05 is a threshold for the output >> g_log_best=edge(f,’ log’,0.003, 2.25); % figure 10.7(d) %0.003 is the output threshold and 2.25 is the standard deviation of the Gaussian >> g_canny_best=edge(f,’canny’, [0.04,0.10],1.5); % figure 10.7(f) %0.04 and 0.10 are the output(More)
We present the results of using the new MATLAB Image Processing Toolbox and the C programming language in a senior-level image processing course at the University oi Illinois. The course includes for the first time a formal lab component, so more time and effort have been devoted to computer algorithm implementation than previously. Students are expected to(More)
A multirate (MR) filter bank is called size-limited if the total number of output samples equals the number of input samples. A method called symmetric extension improved performance in subband image compression systems compared to the earlier method of circular convolution. However, the symmetric extension method was developed only for two-band uniform(More)
Software testing can improve software quality. To test effectively, scientists and engineers should know how to write and run tests, define appropriate test cases, determine expected outputs, and correctly handle floating-point arithmetic. Using Matlab xUnit automated testing framework, scientists and engineers using Matlab can make software testing an(More)
Thresholding and edge detection being one of the important aspects of image segmentation comes prior to feature extraction and image recognition system for analyzing images. It helps in extracting the basic shape of an image, overlooking the minute unnecessary details. In this paper using image segmentation (thresholding and edge detection) techniques(More)
Noise removal plays vital role in image processing and also important pre processing task before performing post operation like Image segmentation etc. . This paper presents a effective and efficient algorithm in order to remove impulse noise from gray scale and color images. Challenging results show the superior performance of the proposed filtering(More)
This paper presents a thorough experimental analysis to investigate the behavior of neural network classifier for classification of multispectral satellite images. For this series of experiments have been performed to study the effect of various neural network parameters upon classification accuracy. It is per pixel supervised classification using spectral(More)
It is an extremely bulky process to predict a disease based on the visual diagnosis of cell type with precision or accuracy, especially when multiple features are associated. If we get the information about the dead skin which is not visible by naked eyes well in time then we can easily prevent the further spreading of disease on the other part of body. One(More)