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Binary codes that are binarizations of features represented by real numbers have recently been used in the object recognition field, in order to achieve reduced memory and robustness with respect to noise. However, binarizing features represented by real numbers has a problem in that a great deal of the information within the features drops out. That is why we focus on quantization residual, which...
Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as object detection, recognition, and tracking. We propose a new method for detecting object boundaries using planar laser scanners (LIDARs) and, optionally, co-registered imagery. We formulate boundary detection as a classification...
Cell segmentation in microscopy imagery is essential for many bioimage applications such as cell tracking. To segment cells from the background accurately, we present a pixel classification approach that is independent of cell type or imaging modality. We train a set of Bayesian classifiers from clustered local training image patches. Each Bayesian classifier is an expert to make decision in its specific...
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