MATLAB and Simulink Based Books - New Textbooks on Clean Energy and Image Processing
Clean energy technologies such as wind turbines, solar arrays, and fuel cells are playing an increasingly important role in energy production. Engineers develop advanced mathematical models and simulations to analyze complex systems based on these technologies in a time-efficient, safe, repeatable environment. Recent textbooks that support these developments include:
By Ali Keyhani, Ohio State University, and Mogammad N. Marwali and Min Dai, Emerson Network Power
John Wiley & Sons, Inc.
By Horacio Perez-Blanco, Penn State University
CRC Press, Inc.
By Francis Vanek and Louis D. Albright, Cornell University
By M. Hashem Nehrir, Montana State University, and Caisheng Wang, Wayne State University
By Colleen Spiegel, Clean Fuel Cell Energy LLC
Image Processing: Morphological Reconstruction
Morphological reconstruction is a useful but little-known method for extracting meaningful information about shapes in an image. The shapes could be just about anything: letters in a scanned text document, fluorescently stained cell nuclei, or galaxies in a far-infrared telescope image. You can use morphological reconstruction to extract marked objects, find bright regions surrounded by dark pixels, detect or remove objects touching the image border, detect or fill in object holes, filter out spurious high or low points, and perform many other operations.
Morphological reconstruction processes one image, called the marker, based on the characteristics of another image, called the mask. The high points, or peaks, in the marker image specify where processing begins. The peaks spread out, or dilate, while being forced to fit within the mask image.
This excerpt from Digital Image Processing Using MATLAB defines morphological reconstruction, illustrates some useful manipulations of binary images, and shows how you can use functions in Image Processing Toolbox™ to quickly perform these manipulations.
By Rafael C. Gonzalez, University of Tennessee, Knoxville; Richard E. Woods, MedData Interactive; and Steven L. Eddins, MathWorks