中文 English
Home
TECHNICAL PAPERS

A Novel Power-Saving Reversing Camera System with Artificial Intelligence Object Detection

Researchers propose a reversing camera system with AI object detection to increase the information of the reversing image, with a “image processing chip with wide-angle image distortion correction and an image buffer controller, a low-power KL520 chip and an optimized AI model MobileNetV2-YOLOV3-Optimized (MNYLO).”

popularity

Abstract

“According to a study by the Insurance Institute for Highway Safety (IIHS), the driving collision rate of using only the reversing camera system is lower than that of using both the reversing camera system and the reversing radar. In this article, we implemented a reversing camera system with artificial intelligence object detection to increase the information of the reversing image. Our system consists of an image processing chip (IPC) with wide-angle image distortion correction and an image buffer controller, a low-power KL520 chip and an optimized artificial intelligence model MobileNetV2-YOLOV3-Optimized (MNYLO). The results of the experiment show the three advantages of our system. Firstly, through the image distortion correction of IPC, we can restore the distorted reversing image. Secondly, by using a public dataset and collected images of various weathers for artificial intelligence model training, our system does not need to use image algorithms that eliminate bad weathers such as rain, fog, and snow to restore polluted images. Objects can still be detected by our system in images contaminated by weather. Thirdly, compared with the AI model Tiny_YOLOV3, not only the parameters of our MNYLO have been reduced by 72.3%, the amount of calculation has been reduced by 86.4%, but the object detection rate has also been maintained and avoided sharp drops.”

Find the open access technical paper here. Published Jan. 2022.

Hung, K.-C.; Lin, M.-C.; Lin, S.-F. A Novel Power-Saving Reversing Camera System with Artificial Intelligence Object Detection. Electronics 2022, 11, 282. https://doi.org/10.3390/electronics11020282.

Visit Semiconductor Engineering’s Technical Paper library here and discover many more chip industry academic papers.



1 comments

reyhan says:

thanks alot of information

Leave a Reply


(Note: This name will be displayed publicly)