Berthold K.P. Horn

Berthold K. P. Horn is Professor of Electrical Engineering and Computer Science at MIT. He has presided over the field of machine vision for more than a decade and is the author of Robot Vision.

  • Shape From Shading

    Shape From Shading

    Berthold K.P. Horn and Michael J. Brooks

    Understanding how the shape of a three dimensional object may be recovered from shading in a two-dimensional image of the object is one of the most important—and still unresolved—problems in machine vision. Although this important subfield is now in its second decade, this book is the first to provide a comprehensive review of shape from shading. It brings together all of the seminal papers on the subject, shows how recent work relates to more traditional approaches, and provides a comprehensive annotated bibliography.

    The book's 17 chapters cover: Surface Descriptions from Stereo and Shading. Shape and Source from Shading. The Eikonal Equation: some Results Applicable to Computer Vision. A Method for Enforcing Integrability in Shape from Shading Algorithms. Obtaining Shape from Shading Information. The Variational Approach to Shape from Shading. Calculating the Reflectance Map. Numerical Shape from Shading and Occluding Boundaries. Photometric Invariants Related to Solid Shape. Improved Methods of Estimating Shape from Shading Using the Light Source Coordinate System. A Provably Convergent Algorithm for Shape from Shading. Recovering Three Dimensional Shape from a Single Image of Curved Objects. Perception of Solid Shape from Shading. Local Shading Analysis Pentland. Radarclinometry for the Venus Radar Mapper. Photometric Method for Determining Surface Orientation from Multiple Images.

    Shape from Shading is included in the Artificial Intelligence series, edited by Michael Brady, Daniel Bobrow, and Randall Davis.

    • Hardcover $85.00
    • Paperback $55.00
  • Robot Vision

    Robot Vision

    Berthold K.P. Horn

    This book presents a coherent approach to the fast moving field of machine vision, using a consistent notation based on a detailed understanding of the image formation process. It covers even the most recent research and will provide a useful and current reference for professionals working in the fields of machine vision, image processing, and pattern recognition. An outgrowth of the author's course at MIT, Robot Vision presents a solid framework for understanding existing work and planning future research. Its coverage includes a great deal of material that important to engineers applying machine vision methods in the real world. The chapters on binary image processing, for example, help explain and suggest how to improve the many commercial devices now available. And the material on photometric stereo and the extended Gaussian image points the way to what may be the next thrust in commercialization of the results in this area. The many exercises complement and extend the material in the text, and an extensive bibliography will serve as a useful guide to current research.

    ContentsImage Formation and Image Sensing •Binary Images: Geometrical Properties; Topological Properties • Regions and Image Segmentation • Image Processing: Continuous Images; Discrete Images • Edges and Edge Finding • Lightness and Color • Reflectance Map: Photometric Stereo Reflectance Map; Shape from Shading • Motion Field and Optical Flow • Photogrammetry and Stereo • Pattern Classification • Polyhedral Objects • Extended Gaussian Images • Passive Navigation and Structure from Motion • Picking Parts out of a Bin

    • Hardcover $111.00
    • Paperback $19.75