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Texture descriptors are a powerful tool for 2D scene features extraction. They can be computed for whole image or for regions of interests obtained from various object detection methods. In case when foreground objects mask obtained from background subtraction or optical-flow thresholding is to be used, the connected components analysis is needed first. The texture descriptor is then computed for...
For the real-time detection and identification requirements of the rail profile image, A quickly algorithm using connectivity labeling of binary image and parameter extracting to remove the speckle disturbing was presented in this paper, based on FPGA, it can use the limited hardware resources of the system to realize high-speed and accurate binary image labeling and feature extraction, obtain the...
We present in this work an image component labeller-and feature extraction module that can operate in real-time. This labeller is suitable for smart cameras and Field Programmable Gate Arrays (FPGA). We show in our work how complex gray value features of image components can be calculated in parallel with label assignment without first resolving complex chains of merged labels. The labeller and a...
Classical connected components labelling algorithms are unsuitable for real-time processing of streamed images on an FPGA because they require two passes through the image. Recently, a single-pass algorithm was proposed that avoided the need to buffer an intermediate image. In this paper, a new single pass algorithm is described that is a considerable improvement over the existing algorithms. The...
Classical connected components labelling algorithms are unsuitable for real-time processing of streamed images on an FPGA because they require two passes through the image. The basic requirements of connected components analysis are investigated, and this led to a novel single-pass approach that avoids the need to buffer an intermediate image. This is further analysed to give an algorithm that is...
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