In experimental tests, apart from obtaining the normal data with allowable errors, the experimenters usually get some unexpected wrong data called “defect marks”. Following the routine method of experimental data processing, the method of bad point exclusion based on automatic programming is seldom taken into consideration by experimenters. This article presents a new method based on the Hough transform to reject bad points. The method is fit for processing data with linear characteristics and can be extended to deal with the data that is possible to be translated into a linear form through functional transformations; curved lines, which can well be processed by the Hough transformation, can be its application too. Simulation experiments and practical applications  manifest that the method raised in this paper performs robustly.