The purpose of this study is to identify vehicles by detecting lights based on extremas in nighttime. This method has focused on headlights of vehicle that are high brightness and taillights of vehicle that are red in nighttime. Headlights are detected by grayscale images, and taillights are detected by red extracted images. In fact, The usefulness of this method is confirmed by using invehicle camera images.

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There is a need for methods to recognize night pedestrian to reduce pedestrian traffic accidents at night. In this paper, we proposed the method that converts images using continuous nighttime images from in‐vehicle camera. The proposed method performs feature extraction that does not depend on one's own vehicle speed because inputting continuous nighttime images, and the function of convolution layer that performs dimensionality reduction. In order to confirm the effectiveness of the proposed method, we prepared the images of simulation and camera. The nighttime images were conversed with the proposed method. After conversion, we calculated the recognition performance by applying object detection which is an object recognition method. We showed the proposed method is more robust against the own vehicle speed change.