Automatically Segmentation the Car Parts and Generate a Large Car Texture Images

Abstract

: This study is segmentation the car parts in a car model data collection and then use the segment car parts to generate large car texture images to provide automatic detection and classification of future 3D car models. The segmentation of car parts proposed in this study is divided into simple and fine car parts segmentation. Since there are few texture images of car parts, this study produces various parts to generate many automobile texture images. First, segment the parts after texture images in an automated method, change the RGB arrangement, change the color, and rotate the parts differently. Also, this study made various changes to the background, and then it randomly combined large texture images with various parts and the background. In the experiment, the car parts were divided into 6 categories: the left door, the right door, the roof, the front body, the rear body, and the wheels. In the performance of automated car parts segmentation technology, the simple and fine car parts segmentation has good results in texture images. Next, the segment car parts and use multiple groups to generate large car texture images automatically. It is hoped that we can practically apply these results to simulation systems.