Aircraft detachable hatch covers are usually fixed via quick-release screws. Given the number of screws on one hatch cover, it is possible that some of them are forgotten to be tightened (i.e., faulty screws) after the inspection because of careless and overtiredness of ground crews, which may lead to security risks. In this paper, a method based on image recognition is proposed to identify faulty screws. By analyzing the characteristics of the hatch cover images, image threshold segmentation, dilation and erosion operations are firstly used to pre-process the image. Then, every screw section can be approximately located. A series of sub-images each containing only one complete screw are divided from the original image. After that, Hough transformation is adopted to calculate the longest line in each sub-image. Based on the comparative result of the longest line and the predetermined threshold, whether the screw is faulty can be determined. Then, the proposed method is applied to a hatch cover, which shows that it is effective to faulty screws recognition.