Geometric shape detection in an image is a classical problem that leads to many applications, in cartography to highlight roads in a noisy image, in medical imaging to localize disease in a region and in agronomy to fight against weeds with pesticides. The Hough Transform method contributes effectively to the recognition of digital objects, as straight lines, circles and arbitrary objects. This paper deals with the theoretical comparisons of object dual based on the definition of Standard Hough Transform. It also focuses on parallelism of Hough Transform. A generic pseudo-code algorithm, using the Openmp library for the parallel computing of object dual is proposed in order to improve the execution time. In simulation, a triangular mesh superimposed on the image is implemented with the pymp library in python, in considering threads as inputs to read the image and to update the accumulator. The parallel computing presents reduction of the execution time accordingly to the rate of lit pixels in each virtual object and the number of threads. In perspectives, it will contribute to strenghen the developement of a toolkit for the Hough Transform method.

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