1st Edition

Image Processing Recipes in MATLAB®

    262 Pages 90 Color & 40 B/W Illustrations
    by Chapman & Hall

    262 Pages 90 Color & 40 B/W Illustrations
    by Chapman & Hall

    262 Pages 90 Color & 40 B/W Illustrations
    by Chapman & Hall

    Leveraging the latest developments in MATLAB and its image processing toolbox, this 'cookbook' is a collection of 30 practical recipes for image processing, ranging from foundational techniques to recently published algorithms. Presented in a clear and meaningful sequence, these recipes are prepared with the reader in mind, allowing one to focus on particular topics or read as a whole from cover to cover.

    Key Features:

    • A practical, user-friendly guide that equips researchers and practitioners with the tools to implement efficient image processing workflows in MATLAB.
    • Each recipe is presented through clear, step-by-step instructions and rich visual examples.
    • Each recipe contains its own source code, explanations, and figures, making the book an excellent standalone resource for quick reference.
    • Strategically structured to aid sequential learning, yet with self-contained chapters for those seeking solutions to specific image processing challenges.

    The book serves as a concise and readable practical reference to deploy image processing pipelines in MATLAB quickly and efficiently. With its accessible and practical approach, the book is a valuable guide for those who navigate this evolving area, including researchers, students, developers, and practitioners in the fields of image processing, computer vision, and image analysis.

    I Basic image processing: Acquisition and visualisation
    Recipe 1: Loading, displayng and saving images
    Recipe 2: Image conversion
    Recipe 3: Image acquisition using a webcam
    Recipe 4: Browsing through images

    II Geometric operations

    Recipe 5: Geometric transformations
    Recipe 6: Image warping

    III Histograms

    Recipe 7: Histograms and statistics of grayscale images
    Recipe 8: Histogram equalization and histogram matching
    Recipe 9: Individual channel histograms of color images
    Recipe 10: Combined color histograms and dominant colors in an image

    IV Point transformations

    Recipe 11: Intensity transformation functions
    Recipe 12: Custom point transformation functions
    Recipe 13: Gamma correction
    Recipe 14: Leveling non-uniform illumination

    V Spatial filtering and special effects

    Recipe 15: Smoothing filters
    Recipe 16: Sharpening filters
    Recipe 17: Other image filters and special effects

    VI Image segmentation

    Recipe 18: Image binarization
    Recipe 19: Region-based segmentation
    Recipe 20: Image segmentation using k-means clustering
    Recipe 21: Superpixel oversegmentation using SLIC
    Recipe 22: Graph-based segmentation

    VII Binary image snalysis

    Recipe 23: Finding, counting, and accessing connected components in binary images
    Recipe 24: Basic morphological operations
    Recipe 25: Computing connected components' features

    VIII Color image processing

    Recipe 26: Converting among different color spaces
    Recipe 27: Color image adjustments
    Recipe 28: Image pseudocoloring

    IX Batch processing and handling large images

    Recipe 29: Processing very large images
    Recipe 30: Batch processing a set of images


    Oge Marques, PhD is a Professor of Computer Science and Engineering in the College of Engineering and Computer Science, a Professor of Biomedical Science (Secondary) in the Charles E. Schmidt College of Medicine, and a Professor of Information Technology (by courtesy), in the College of Business at Florida Atlantic University (FAU) (Boca Raton, FL).

    He is the author of 12 technical books, one patent, and more than 130 refereed scientific articles on image processing, medical image analysis, computer vision, artificial intelligence, and machine learning.

    Dr. Marques is a Senior Member of both the IEEE (Institute of Electrical and Electronics Engineers) and the ACM (Association for Computing Machinery), Fellow of the NIH AIM-AHEAD Consortium, Fellow of the Leshner Leadership Institute of the American Association for the Advancement of Science (AAAS), Tau Beta Pi Eminent Engineer, and member of the honor societies of Sigma Xi, Phi Kappa Phi, and Upsilon Pi Epsilon.

    Gustavo Benvenutti Borba, PhD is an Associate Professor in the Department of Electronics and the Graduate School on Biomedical Engineering at the Federal University of Technology-Paraná (UTFPR) (Curitiba, Brazil).

    He obtained his PhD in Electrical Engineering from UTFPR. He is the author of more than 30 refereed scientific articles on image processing, image retrieval, and related topics.