Abstract
Monocular vision-based passive ranging system is attractive for potential applications in navigation, transportation and traffic control, robotics, and air defense. Conventionally system estimates target distance by using imaging direction and distance-related features, and the latter are extracted from the image sequence. It is not only challenging to DSP device hardware capability but also to programming optimization that to transplant the traditional feature extraction algorithm to a real-time system due to the complexity and time-consuming. In this paper, a simplified scale invariant feature transform image matching algorithm and code optimization procedure are developed, and the improvement of operation speed is demonstrated clearly. For an image sequence with size of \(256\times 256\) pixels, the operation speed was improved to 25–27 frames per second from 4 s per frame by using a single C64x+ DSP core, which meets the requirements of real-time ranging algorithm perfectly while the ranging error is less than \(7\,\%\).
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