Real object recognition using moment invariants

Moment Invariants for Object Recognition

Generalized affine moment invariants for object recognition

This paper introduces a new way of extracting affine invariant features from image functions. The presented approach is based on combining affine moment invariants (AMI) with multiscale invariants, in particular multiscale autoconvolution (MSA) and spatial multiscale affine invariants (SMA). Our approach includes all of these invariants as special cases, but also makes it possible to construct ...

Object Recognition Based on Moment (or Algebraic) Invariants

Toward the development of an object recognition and positioning system, able to deal with arbitrary shaped objects in cluttered environments, we introduce methods for checking the match of two arbitrary curves in 2D or surfaces in 3D, when each of these subobjects (i.e., regions) is in arbitrary position, and we also show how to efficiently compute explicit expressions for the coordinate transf...

Generalized Rotational Moment Invariants For Robust Object Recognition

High-order Hu moment invariant functions have always been required to solve a variety of problems. Up to this point, there was no generalized approach to extend the first six Hu moment invariants to higher orders. Therefore, this paper presents a generalized algorithm to determine rotationally invariant Hu moment invariants of any desired order, which are invariant to scaling, translation and r...

Using Photometric Invariants for 3D Object Recognition

In this paper we describe a new efficient algorithm for recognizing 3D objects by combining photometric and geometric invariants. We derive some photometric properties that are invariant to the changes of illumination and to relative object motion with respect to the camera and/or the lighting source in 3D space. We show that recognition does not require a full constancy of colors; rather, it o...