Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and Pentium IV classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a significant speedup can be achieved comparing to sequential code. PCs, mainly employing Intel Pentium processors, are the most commonly available and inexpensive solutions to many applications. Therefore, the performance of SSE in common image and signal processing algorithms has been studied extensively in the literature. Nevertheless, most of the studies concerned with low-level image processing algorithms, which involves pixels in pixels out type of operations. In this paper, we study higher-level image processing algorithms where image features and recognition is the output of the operations. Hough transform sand Geometric hashing techniques are commonly used algorithms for this purpose. Here, their implementation using SSE are presented.
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