The roller missing defect in the assembling process of deep groove ball bearings is detected automatically with the machine vision method. Three lighting schemes are presented for acquisition of bearing images. The image noise is removed by median filter. The Hough transform algorithm and the polar coordinate expansion method are used for circular detection and rectangular expansion of bearing images. 80 perfect bearings and 60 roller missing bearings are selected for test. The results show that the lighting system of coaxial light source combined with backlight can effectively reduce the surface reflection of bearings. The pre-processing of the image with the median filter can eliminate the isolated noise and make the image less vague. The Hough transform algorithm can quickly obtain the images of bearing inner and outer rings and locate them. The Cartesian polar coordinate expansion method can expand the roller bearing images into rectangles. The detection and recognition of the roller missing position are realized by setting the gray threshold. The recognition rates of the proposed method for 80 perfect bearings and 60 roller missing bearings are 92.5% and 93.3%, respectively.