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This paper presents a novel concurrent algorithm for object detection based on the Hough Transform. The Generalized Hough Transform can detect object contours regardless of scale and orientation, but has a computational complexity of O(N2RS), where N, R, and S are the array dimensions for X/Y, rotation, and scale, respectively. The high complexity makes it impossible to perform object detection in real-time. In our work, we propose a modified, concurrent algorithm using a multi-threading technique with manager-worker scheme to obtain a reduced complexity of O(N2/M) where M is the number of processors. Our new algorithm utilizes multi-threading technology to enhance the computing speed. The algorithm is evaluated from both the perspective of output image quality and performance scalability.