A supervised neural network approach to invariant image recognition (original) (raw)

Icarcv 2004 8th Control Automation Robotics and Vision Conference 2004, 2004

Abstract

Invariant image recognition is one of the hardest problems in computer vision. The aim is to identify an image independently of its rotational orientation and size, as well as changing its color intensity. The current techniques such as high-ordered neural network and Zernike moments are not practical to apply to color images of size at least 256 × 256 pixels.

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