Headquartered in Germany, our client is the research and development center for the world’s largest manufacturer of premium and commercial vehicles. The center focuses on research, IT engineering, and product development.
As a critical component for vehicle performance and stability, automobile manufacturers implement specialized inspection processes to ensure the integrity and quality of tires. Frequent quality checks on aspects such as tread depth, sidewall texture, and rigidity help determine the quality of a tire. The tire inspection system enables tread depth measurement using a mobile application. A deep learning model based on Convolutional Neural Network (CNN) was implemented and trained on thousands of images. Deep learning and traditional computer vision approaches were used to develop a custom CNN architecture that rendered the desired accuracy in tread depth measurement.