Machine Vision Sensors

Machine vision

This text is intended to provide a balanced introduction to machine vision. Basic concepts are introduced with only essential mathematical elements. The details to allow implementation and use of vision algorithm in practical application are provided, and engineering aspects of techniques are emphasized. This text intentionally omits theories of machine vision that do not have sufficient practi...

Panomorph Based Panoramic Vision Sensors

Multispectral Sensors in Computer Vision

The majority of color work in machine vision has been based on a trichromatic (and specifically RGB) color representation. In reality, color is a continuous univariate function of wavelength which can be quantized into an arbitrary number of dimensions. The capture of reflectance information in spectrally higher dimensions will improve image analysis. To acquire spectrally and spatially highdim...

Machine Learning, Machine Vision, and the Brain

The problem of learning is arguably at the very core of the problem of intelligence, both biological and artificial. In this paper we review our work over the last ten years in the area of supervised learning, focusing on three interlinked directions of research: theory, engineering applications (making intelligent software) and neuroscience (understanding the brain’s mechanisms of learning) wh...

Shape Based Machine Vision

The study of visual object recognition is often motivated by the problem of recognizing 3-d objects given that we receive 2-d patterns of light on our retinae. Recent findings from human psychophysics, neurophysiology and computational vision provide converging evidence for a view-based recognition framework in which objects and scenes are represented as collections of viewpoint-specific local ...