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Directional Ringlet Intensity Feature Transform For Tracking, Evan Krieger, Paheding Sidike, Theus H. Aspiras, Vijayan K. Asari
Directional Ringlet Intensity Feature Transform For Tracking, Evan Krieger, Paheding Sidike, Theus H. Aspiras, Vijayan K. Asari
Vijayan K. Asari
The challenges existing for current intensity-based histogram feature tracking methods in wide area motion imagery include object structural information distortions and background variations, such as different pavement or ground types. All of these challenges need to be met in order to have a robust object tracker, while attaining to be computed at an appropriate speed for real-time processing. To achieve this we propose a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), that employs Kirsch kernel filtering and Gaussian ringlet feature mapping. We evaluated the DRIFT on two challenging datasets, namely Columbus Large Image Format (CLIF) and Large Area Image …
Histogram Of Oriented Phase (Hop): A New Descriptor Based On Phase Congruency, Hussin Ragb, Vijayan K. Asari
Histogram Of Oriented Phase (Hop): A New Descriptor Based On Phase Congruency, Hussin Ragb, Vijayan K. Asari
Vijayan K. Asari
In this paper we present a low level image descriptor called Histogram of Oriented Phase based on phase congruency concept and the Principal Component Analysis (PCA). Since the phase of the signal conveys more information regarding signal structure than the magnitude, the proposed descriptor can precisely identify and localize image features over the gradient based techniques, especially in the regions affected by illumination changes. The proposed features can be formed by extracting the phase congruency information for each pixel in the image with respect to its neighborhood. Histograms of the phase congruency values of the local regions in the image …