Invariance to various transformations is key to object recognition but existing definitions of invariance are somewhat confusing while discussions of invariance are often confused. In this report, we provide an operational definition of invariance by formally defining perceptual tasks as classification problems. The definition should be appropriate for physiology, psychophysics and computationa...

Vision relies on constancy mechanisms. Yet, these are little understood, because they are difficult to investigate in freely moving organisms. One such mechanism, translation invariance, enables organisms to recognize visual patterns independent of the region of their visual field where they had originally seen them. Tethered flies (Drosophila melanogaster) in a flight simulator can recognize v...

In this paper, we use the weighted distance between fuzzy numbers to investigate the approximation of arbitrary fuzzy numbers by weighted distance. We then discuss properties of the approximation strategy including continuity, translation invariance, scale invariance and identity and give an application to the generation of fuzzy partitions. 2006 Elsevier Inc. All rights reserved.

Maloney and Ahumada [9] have proposed a network learning algorithm that allows the visual system to compensate for irregularities in the positions of its photoreceptors. Weights in the network are adjusted by a process tending to make the internal image representation translationinvariant. We report on the behavior of this translation-invariance algorithm calibrating a visual system that has lo...

301 We describe a method of constructing higher-order neural networks that respond invariantly under geometric transformations on the input space. By requiring each unit to satisfy a set of constraints on the interconnection weights, a particular structure is imposed on the network. A network built using such an architecture maintains its invariant performance independent of the values the weig...

This paper presents a novel algorithm, called Radial Sector Coding (RSC), for Translation, Rotation and Scale invariant character recognition. Translation invariance is obtained using Center of Mass (CoM). Scaling invariance is achieved by normalizing the features of characters. To obtain most challenging rotation invariance, RSC searches a rotation invariant Line of Reference (LoR) by exploiti...