Proceedings PaperGabor wavelet filters and fusion for distortion-invariant multiclass object detection
|Format||Member Price||Non-Member Price|
Several different new Gabor wavelet filters are described: the Gabor transform (GT) filter consists of real, imaginary, and clutter filters; the Gabor basis function (GBF) filter uses a Gabor basis function for each training image; the morphological wavelet transform (MWT) filter includes a Gabor transform clutter map filter that locates clutter regions of a scene. These filters ar all shift-invariant and distortion-invariant. They are employed for detection: location of the positions of all object regions of interest (ROIs) in an input scene. Fusion of multiple filter outputs is used to reduce false alarms. This paper emphasizes the role for Gabor wavelet filters in detection and for producing a clutter map. Major emphasis is given to the final version of the Gabor wavelet clutter map portion of our MWT algorithm (this is our best detection algorithm). New detection and fusion results with a consistent database and thresholds are provided.