One of the most challenging tasks in stereopsis is to find corresponding points in a stereo image pair to obtain depth information. Half occlusion and order-reversal of objects further complicate the problem. In this paper, we propose the use of hue and intensity of images for stereo correspondences. Stereo correspondence is performed row by row. Planar first-order least squares curve-fitting is exploited to extract line-segments with similar hue. A sloping intensity profile of line-segment is used to indicate the presence of a sloping surface with the same hue. A Left-Left Right-Right (LL-RR) constraint is introduced for matching line-segment pair: the possible occluded part should be located both at the leftmost part of the left-line-segment and at the rightmost part of the right-line-segment. This constraint is used to detect half-occlusion in line-segment pair matching. Finally, an object is formed from a block of contiguous line-segments separated from other blocks by gaps. Experiments were performed on stereo image pairs and the estimated disparity maps are used to evaluate the performance of the proposed algorithm.
Airborne or vehicle-borne sensor-based techniques are potentially attractive approaches for fast detection of landmine field towards efficient and safety humanitarian demining. The measured data in such cases has a rather low spatial resolution due to the altitude of measurements. Landmines in an IR image are either indicated directly due to their temperature difference to background, or indirectly by signs of digging or disturbance patterns. This paper proposes a novel method for automatically detecting landmine candidates by exploiting features associated with landmine point patterns. We describe a special type of multiresolution isotropic bandpass filter for detecting these landmine candidates and other man-made landmarks on the ground surface (which may be used for locating mine fields). The introduction of multiresolution to the detection fiber enables both good detectability and localization of landmine candidates. However, the method cannot distinguish landmine candidates from clutter sharing similar spatial patterns. Therefore, it is only suitable for detecting landmine fields, or candidates of landmines. For reliable individual mine detection, landmine discrimination methods should be subsequently applied. Experiments were performed on several images measured from vehicle-borne and airborne sensors over the test bed scenarios, and some results are included.
In this paper we present an overview of various strategies for image segmentation, showing their advantages and drawbacks. The overview covers most of the methods from the classical statistical methods to model-based techniques, with a focus on color images. The paper concludes with a summary of our approach to identifying interreflection.
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