Development of Computer Vision Algorithms for Nanoscale Contact Detection

The client faces significant difficulties in accurately estimating contact points between nanometer-scale objects due to optical limitations inherent at such dimensions, impacting quality control and experimental analysis processes at the nanoscale level.

A high-tech manufacturing company specializing in nanotechnology-based products requiring precise contact point estimation between nanoscale objects.

• Develop robust computer vision algorithms capable of estimating contact points between nanoscale objects based on RGB image sequences.
• Overcome optical limitations in imaging at the nanoscopic scale by leveraging differential frame analysis and machine learning techniques.
• Integrate sensor data from servo-motor mounted sensors to improve accuracy of contact point estimation.
• Achieve a high level of precision in contact detection, aiming to reliably detect differences as small as 2 nanometers.

• Analysis of RGB image sequences to detect changes in outer shape of objects through differential frame analysis.
• Application of machine learning models trained on image difference data to estimate contact points with high precision.
• Fusion of visual data with sensor measurements from mounted servomotors to enhance estimation accuracy.
• Real-time processing capability for continuous contact monitoring during nanoscale interactions.

• RGB camera recording systems
• Sensor modules mounted on actuators/servomotors for positional data

• Real-time processing to enable immediate feedback during nanoscale experiments
• High accuracy with estimation errors below 2 nanometers
• System scalability to handle high-resolution image data
• Robustness against optical limitations and noise inherent at nanoscale

The implementation of these computer vision and sensor fusion algorithms is expected to significantly enhance nanoscale contact detection precision, enabling more accurate and reliable measurements. This is projected to lead to improved product quality, accelerated research and development cycles, and potentially reduce operational costs associated with nanoscale imaging inaccuracies.