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Introduction to image processing using R : learning by examples
Frery A., Perciano T., Springer Publishing Company, Incorporated, New York, NY, 2013. 102 pp. Type: Book (978-1-447149-49-1)
Date Reviewed: Jul 26 2013

The statistical software R proves to be a powerful solution for various fields, including image processing, where efficient R packages are available.

This book addresses the basic use of R for image processing in six short chapters. The first chapter presents fundamental concepts and notations, both for single and multiband images, and basic statistical analysis using R.

Chapter 2 is independent of R and describes very briefly the color representation (RGB, CMYK, and HSV) models and both vector--portable document format (PDF), PostScript (PS), and scalable vector graphics (SVG)--and raster--TIFF, JPEG, portable network graphics (PNG), and BMP--formats. The third chapter explores the reading and writing of images with R when some packages are invoked: grDevices, grImport, Inkscape, PixMap, PNG, rtiff, ReadImages, EBImage, BMP, PS, PDF, SVG, JPEG, and grid.

Chapter 4 discusses basic methods for contrast manipulation using R, and chapter 5 describes the filtering process aided by R, including both convolution- and order-statistics-based filters. The last chapter shows how principal components can be used for contrast enhancement and dimensionality reduction.

I did notice a few typographical errors in the last two chapters, where the figures are not well identified.

The reader is invited to experiment with the ideas in the book and to extend the investigation, aided by a chapter-by-chapter list of relevant references. The index is well designed and the presentation of the subject is adequate, given the short length of the chapters.

Both professionals and students in image processing or statistical data analysis could use this book as a good guide to using R for image processing.

Reviewer:  G. Albeanu Review #: CR141399 (1310-0886)
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