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This paper presents a new feature point detector that is accurate, efficient and fast. A detailed qualitative evaluation of the proposed feature point detector for gray scale images is then carried out in support of the proposed technique. Experiments have proved that this feature point detector is robust to affine transformations, noise and perspective deformations. More over the proposed detector requires only 28 additions per pixel to evaluate the interest point and its strength, making it one of the fastest feature detectors. The accuracy, speed and parallelizability of this algorithm makes it a strong contender for hardware implementations and applications requiring real time feature point abstraction.