title: Biomimetic machine vision system.
abstract: Real-time application of digital imaging for use in machine vision systems has proven to be prohibitive when used within control systems that employ low-power single processors without compromising the scope of vision or resolution of captured images. Development of a real-time machine analog vision system is the focus of research taking place at the University of Wyoming. This new vision system is based upon the biological vision system of the common house fly. Development of a single sensor is accomplished, representing a single facet of the fly's eye. This new sensor is then incorporated into an array of sensors capable of detecting objects and tracking motion in 2-D space. This system "preprocesses" incoming image data resulting in minimal data processing to determine the location of a target object. Due to the nature of the sensors in the array, hyperacuity is achieved thereby eliminating resolutions issues found in digital vision systems. In this paper, we will discuss the biological traits of the fly eye and the specific traits that led to the development of this machine vision system. We will also discuss the process of developing an analog based sensor that mimics the characteristics of interest in the biological vision system. This paper will conclude with a discussion of how an array of these sensors can be applied toward solving real-world machine vision issues.
authors.affiliation: Department of Electrical and Computer Engineering, University of Wyoming, Laramie, Wyoming 82071, USA.
authors.forename: William M
authors.initials: WM
authors.lastname: Harman
authors.forename: Steven F
authors.initials: SF
authors.lastname: Barrett
authors.forename: Cameron H G
authors.initials: CH
authors.lastname: Wright
authors.forename: Michael
authors.initials: M
authors.lastname: Wilcox
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D040761:Biomimetic Materials; D004867:Equipment Design; D006793:Houseflies / Q000502:physiology*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009716:Numerical Analysis, Computer-Assisted; D009799:Ocular Physiological Phenomena; D010363:Pattern Recognition, Automated / Q000379:methods*; D010786:Photoreceptor Cells / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D014785:Vision, Ocular / Q000502:physiology*