Abstract

A scale invariant 3D object detection method based on phase Fourier transform (PhFT) is addressed. Three-dimensionality is expressed in terms of range images. The PhFT of a range image gives information about the orientations of the surfaces in the 3D object. When the object is scaled, the PhFT becomes a distribution multiplied by a constant factor which is related to the scale factor. Then 3D scale invariant detection can be solved as illumination invariant detection process. Several correlation operations based on vector space representation are applied. Results show the tolerance of detection method to scale besides discrimination against false objects.

Highlights

  • Recent interest in three-dimensional (3D) optical information systems has increased because of its vast potential in applications such as object recognition, image encryption as well as 3D display [1]

  • Techniques based on Fourier transform profilometry (FTP) are used for 3D object detection [7,8]

  • In this paper we have addressed scale invariant 3D object detection using the phase Fourier transform (PhFT) applied to range imagery in combination with nonlinear statistical operations that we have defined recently for intensity invariant 2D pattern recognition [18,19]

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Summary

Introduction

Recent interest in three-dimensional (3D) optical information systems has increased because of its vast potential in applications such as object recognition, image encryption as well as 3D display [1]. The idea is to detect the planar surface of a 3D range image when the Fourier transform of a phase-coded image (the phase being proportional to the elevation) is calculated using feed-forward neural networks [14] Another application of this technique is face recognition applications, for which the range image plays an important role since it contains richer and more accurate shape information than 2D intensity images [16]. The method suffers from complexity and a certain limitation of the space bandwidth product To avoid such inconveniences, the use of PhFT of range images is studied for shift, rotation and scale invariance using feed-forward neural networks [14]. In this paper we have addressed scale invariant 3D object detection using the PhFT applied to range imagery in combination with nonlinear statistical operations that we have defined recently for intensity invariant 2D pattern recognition [18,19].

Scale changes for range image phase Fourier transforms
Intensity invariant correlation method
Results of detection

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