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Image encoding using interest points is a common technique in computer vision. In this paper we present a scale and rotation invariant shape centered interest point (SCIP) detector. By means of detecting singularities in Gradient Vector Flow (GVF) fields we find points of high symmetry in the image. Due to the nature of the underlying GVF field we can employ our features to group together edge-based...
The extraction of lane mark is an essential step for several vision-based systems in intelligent transportation applications. In this paper, we propose a novel method for lane detection using a new active contour model. The new model is a modified version of the classical C-V model in gradient domain. The initial level set curve can be anywhere in the image without changing the segmentation result...
We propose a novel set of medial feature interest points based on gradient vector flow (GVF) fields [18]. We exploit the long ranging GVF fields for symmetry estimation by calculating the flux flow on it. We propose interest points that are located on maxima of that flux flow and offer a straight forward way to estimate salient local scales. The features owe their robustness in clutter to the nature...
Statistical properties of high-resolution overhead images representing different land use categories are analyzed using various local and global statistical image properties based on the shape of the power spectrum, image gradient distributions, edge co-occurrence, and inter-scale wavelet coefficient distributions. The analysis was performed on a database of high-resolution (1 meter) overhead images...
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