Inferior Alveolar Nerve canal(IAC) is most sensitive nerve canal and it should be avoided during the surgery of impacted wisdom tooth and applications like dental implants and detection of IAC plays an important role in dental surgery. This paper proposes an automated approach for detection of IAC in the mandibular region, which is vital for Oral and Maxillofacial surgery. The proposed algorithm comprises Contrast-Limited Adaptive Histogram Equalization (CLAHE) to improve the visibility of the input image. The B-Spline method is used to disconnect the upper and lower jaws, and Vertical Integral Projection is used to divide the lower jaw into two sections. Fuzzy Inference system for edge detection is used to extract the far range of edges from the segmented preprocessed image. BRISK (Binary Robust Invariant Scalable Key points) feature descriptor is used to detect feature point location of the nerve canal from Edge detected image. Then the locations of the points are connected and the IAC is detected using curve fitting approach. This algorithm provides better results compared with ground truth image and it has an ability to detect the alveolar nerve canal successfully.