Image Shifting Tracking Leveraging Memristive Devices

Unconventional circuits with built-in memory and computing functionalities are becoming the cornerstones of artificial intelligence (AI) at the edge. In the currently deployed systems, sensing and computing occur in separate physical locations, imposing a vast amount of data shuttling between the sensor module and the cloud-computing platforms. Regarding the acceleration of image processing at the edge, in this work, a memristive computing circuit has been designed. By exploiting the non-linear behavior and memory capabilities of memristor devices, a memristive circuit, capable of tracking the shifting of an image is proposed. The presented circuit design can be also combined with an array of sensors, aiming to implement a discrete image tracking module.

Theodoros Panagiotis Chatzinikolaou, Iosif-Angelos Fyrigos, Georgios Ch. Sirakoulis