In this paper, we propose the use of modified Hough transforms to efficiently extract object feature parameters, which are usually contaminated by heavily noisy corrugation and discontinuity. The modified HT (MHT) is developed by introducing spatial and parameter weighting functions to imporve the detection performance for the traditional Hough transform (HT), which generally fails to robustly detect natural object parameters. Using designed test patterns and real images, simulations show that the proposed weighting functions are helpful in detecting noise-corrupted objec features. Due to its robustness, the MHT can be easily figured with a coarse-to-fine adaptive search mechanism to reduce the huge amount of computation for feature parameters extraction.