A Method for Blur and Affine Invariant Object Recognition Using Phase-Only Bispectrum

Authors:
Ville Ojansivu;Janne Heikkilä
Affiliations:
Machine Vision Group, Department of Electrical and Information Engineering, University of Oulu, Finland 90014;Machine Vision Group, Department of Electrical and Information Engineering, University of Oulu, Finland 90014
Venue:
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Year:
2008

Citing 6
Cited 0

Degraded Image Analysis: An Invariant Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence
Pictorial Recognition of Objects Employing Affine Invariance in the Frequency Domain

IEEE Transactions on Pattern Analysis and Machine Intelligence
Affine Invariant Features from the Trace Transform

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Blur and Similarity Transform Invariant Object Recognition

ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Object recognition using frequency domain blur invariant features

SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Recognition of blurred images by the method of moments

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a novel method for recognizing objects in images in a way that is invariant to blur and affine transformation of the images. The method is based on a set of rotated and log-log sampled phase-only bispectrum slices of the images and their phase correlation. The method is invariant to centrally symmetric blur, such as linear motion or out of focus blur. Because of the normalization of the amplitude information, the method is also invariant to uniform illumination changes. The only known method having similar invariance properties is based on image moments. According to the experiments conducted, the proposed method outperforms the moment based method in the presence of various degradations.