A parallel algorithm, in order to extract parametric curves from a two-dimensional (2-D) image space, is proposed. It is based on the Hough transform (HT) and uses the content addressable memory (CAM) as the main processor. A set of simulated results for circular shape extraction are presented in order to demonstrate its merit. Hence, voting, thresholding, and three-dimensional (3-D) peak extraction are efficiently performed within the CAM. In addition, and in order to reduce the quantization errors, a weighted AT algorithm (WHT), which uses a weighted voting is proposed. Experimental results indicate that a real-time shape extraction for an image 256×256 can be achieved within a small amount of hardware. Therefore, CAM-based HT can be considered as a promising attraction for next generation pattern recognition platforms.