Author :
Publisher :
ISBN 13 :
Total Pages : 214 pages
Book Rating : 4.:/5 (115 download)
Book Synopsis Design and Applications for a Multi-cartridge Fly Eye Vision Sensor by :
Download or read book Design and Applications for a Multi-cartridge Fly Eye Vision Sensor written by and published by . This book was released on 2019 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Previous research efforts have shown that the compound vision system of a common house fly, Musca domestica, is capable of improved motion detection and tracking capabilities when compared to traditional camera systems. Especially in applications requiring object detection, obstacle avoidance, and quick visual data processing, these compound vision sensors are more suitable as compared to the usual mammalian inspired vision systems. Proof-of-concept has shown that even without using a computer processing system, existing compound vision sensors can mimic the motion hyperacuity characteristic of the fly's visual system and at the same time provide near instantaneous edge detection and motion tracking. However, the existing sensor design consists of seven photodiodes which generate artifacts in the output signal. This type of sensor design has been implemented in analog circuitry and was found to have limited capability to detect different types of edges. Therefore, to advance the state-of-art of existing fly eye vision sensors, certain design changes were done in this work to avoid these signal artifacts. Moreover, a digital equivalent of the existing analog circuitry has been designed and tested without losing the motion hyperactivity characteristic of the sensor. Furthermore, for the existing seven photodiode sensor designs, an improved edge detection algorithm has been designed that correctly classifies horizontal and vertical edges as the previous design could but can now also correctly detect and classify diagonal edges. Taking a step further, a multi-cartridge sensor design has been proposed that can further enhance the sensor's capability to detect single edges as well as correctly classify the corners present in the sensor's field-of-view.