This paper presents a new representation called "hierarchical Gabor filters" and associated novel local measures which are used to detect potential objects of interest in images. The "first stage" of the approach uses a wavelet set of wide-bandwidth separable Gabor filters to extract local measures from an image. The "second stage" makes certain spatial groupings explicit by creating small-bandwidth, non-separable Gabor filters that are tuned to elongated contours or periodic patterns. The non-separable filter responses are obtained from a weighted combination of the separable basis filters, which preserves the computational efficiency of separable filters while providing the distinctiveness required to discriminate objects from clutter. This technique is demonstrated on images obtained from a forward looking infrared (FLIR) sensor.<>


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Hierarchical Gabor filters for object detection in infrared images


    Contributors:
    Braithwaite (author) / Bhanu (author)


    Publication date :

    1994-01-01


    Size :

    458632 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Hierarchical Gabor Filters for Object Detection in Infrared Images

    Braithwaite, R. N. / Bhanu, B. / Institute of Electrical and Electronics Engineers; Computer Society | British Library Conference Proceedings | 1994


    Object detection using Gabor responses and texture information in low contrast infrared images

    Sun, Sun-Gu / Park, Sang-Soon / Lee, Jong-Min et al. | Tema Archive | 2008



    Segmentation and Object Detection with Gabor Filters and Cumulative Histograms

    Shioyama, T. / Wu, H. / Mitani, S. et al. | British Library Conference Proceedings | 1999


    Face recognition from 2D and 3D images using 3D Gabor filters

    Wang, Y. / Chua, C. S. | British Library Online Contents | 2005