Sökning: "Gösta Granlund"

Visar resultat 1 - 5 av 18 avhandlingar innehållade orden Gösta Granlund.

  1. 1. Topics in applied pattern recognition

    Författare :Gösta H. Granlund; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : .... LÄS MER

  3. 2. Controllable Multi-dimensional Filters and Models in Low-Level Computer Vision

    Författare :Mats T. Andersson; Gösta Granlund; Linköpings universitet; []
    Nyckelord :TECHNOLOGY; TEKNIKVETENSKAP;

    Sammanfattning : This thesis concerns robust estimation of low-level features for use in computer vision systems. The presentation consists of two parts.The first part deals with controllable filters and models. A basis filter set is introduced which supports a computationally efficient synthesis of filters in arbitrary orientations. LÄS MER

  4. 3. Learning in a Reactive Robotic Architecture

    Författare :Thord Andersson; Gösta Granlund; Linköpings universitet; []
    Nyckelord :TECHNOLOGY; TEKNIKVETENSKAP;

    Sammanfattning : In this licenciate thesis, we discuss how to generate actions from percepts within an autonomous robotic system. In particular, we discuss and propose an original reactive architecture suitable for response generation, learning and self-organization. LÄS MER

  5. 4. Circular Symmetry Models in Image Processing

    Författare :Josef Bigun; Gösta Granlund; Linköpings universitet; []
    Nyckelord :TECHNOLOGY; TEKNIKVETENSKAP;

    Sammanfattning : New methods for feature extraction based on the spectral properties of local neighbourhoods is presented. The spectral behaviour of the neighbourhoods is investigated in the spatial domain using the Parseval relation applied to partial derivative pictures. LÄS MER

  7. 5. Hierarchical curvature estimation in computer vision

    Författare :Håkan Bårman; Gösta Granlund; Linköpings universitet; []
    Nyckelord :TECHNOLOGY; TEKNIKVETENSKAP;

    Sammanfattning : This thesis concerns the estimation and description of curvature for computer vision applications. Different types of multi-dimensional data are considered: images (2D); volumes (3D); time sequences of images (3D); and time sequences of volumes (4D).The methods are based on local Fourier domain models and use local operations such as filtering. LÄS MER