Abstract

The paper starts with a brief discussion of the biological vision system that serves as a model for the three types of vision sensors described later on. A retina-like CCD sensor whose computational properties are embedded in its structure is described first, followed by a CMOS tracking sensor that consists of a fovea for smooth pursuit and a periphery for saccadic motion control. This sensor incorporates logarithmic compression, edge detection, direction-of-motion detection and centroid localization. Finally, a CMOS sensor for the detection of image features is discussed. The sensor extracts lower-level features, such as line orientation, line stops, and intersections, in a hierarchical fashion, similar to what the simple and complex cells do in the biological system.

Keywords:
Computer vision Artificial intelligence Image sensor Computer science Orientation (vector space) Machine vision Tracking (education) CMOS sensor Edge detection Saccadic masking Motion detection Motion (physics) Image processing Eye movement Image (mathematics) Mathematics

Metrics

10
Cited By
0.63
FWCI (Field Weighted Citation Impact)
24
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

CCD and CMOS Imaging Sensors
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Photoreceptor and optogenetics research
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
Neuroscience and Neural Engineering
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
© 2026 ScienceGate Book Chapters — All rights reserved.