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Standard Gaussian mixture modeling (GMM) is a well-known method for image segmentation. However, the pixels themselves are considered independent of each other, making the segmentation result sensitive to noise. To reduce the sensitivity of the segmented result with respect to noise, Markov random field (MRF) models provide a powerful way to account for spatial dependences between image pixels. However,...
In this paper, we present a efficient algorithm for real-time ellipse detection. Unlike Hough transform algorithm that is computationally intense and requires a higher dimensional parameter space, our proposed method reduces the computational complexity significantly, and accurately detects ellipses in realtime. We present a new method of detecting arc-segments from the image, based on the properties...
In this paper we describe a fully integrated, real-time, miniaturized embedded stereo vision system (MESVS-II), which fits within 5times5cm and consumes very low power. This is a significant improvement over the original MESVS-I system in terms of performance, quality and accuracy of results. MESVS-II running at 600MHz per core, is capable of operating at up to 20 fps, which is twice as fast as MESVS-I,...
We have developed a fully integrated, miniaturized embedded stereo vision system (MESVS-I) which fits into a tiny package of 5 times 5 cm and consumes very low power (700 mA @ 3.3 V). The system consists of two small profile CMOS cameras, and a power efficient, dual-core embedded media processor, running at 600 MHz per core. The stereo-matching engine performs sub-sampling, rectification, pre-processing...
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