Improved Fourier Mellin Invariant for Robust Rotation Estimation with Omni-cameras

Spectral methods such as the improved Fourier Mellin Invariant (iFMI) transform have proved faster, more robust and accurate than feature based methods on image registration. However, iFMI is restricted to work only when the camera moves in 2D space and has not been applied on omni-cameras images so far. In this work, we extend the iFMI method and apply a motion model to estimate an omni-camera's pose when it moves in 3D space. This is particularly useful in field robotics applications to get a rapid and comprehensive view of unstructured environments, and to estimate robustly the robot pose. In the experiment section, we compared the extended iFMI method against ORB and AKAZE feature based approaches on three datasets showing different type of environments: office, lawn and urban scenery (MPI-omni dataset). The results show that our method boosts the accuracy of the robot pose estimation two to four times with respect to the feature registration techniques, while offering lower processing times. Furthermore, the iFMI approach presents the best performance against motion blur typically present in mobile robotics.Comment: 5 pages, 4 figures, 1 tabl

Fingerprint Verification Using Spectral Minutiae Representations

Most fingerprint recognition systems are based on the use of a minutiae set, which is an unordered collection of minutiae locations and orientations suffering from various deformations such as translation, rotation, and scaling. The spectral minutiae representation introduced in this paper is a novel method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with template protection schemes that require a fixed-length feature vector. This paper introduces the concept of algorithms for two representation methods: the location-based spectral minutiae representation and the orientation-based spectral minutiae representation. Both algorithms are evaluated using two correlation-based spectral minutiae matching algorithms. We present the performance of our algorithms on three fingerprint databases. We also show how the performance can be improved by using a fusion scheme and singular points

Spectral representation of fingerprints

Most fingerprint recognition systems are based on the use of a minutiae set, which is an unordered collection of minutiae locations and directions suffering from various deformations such as translation, rotation and scaling. The spectral minutiae representation introduced in this paper is a novel method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with a template protection scheme, which requires a fixed-length feature vector. This paper introduces the idea and algorithm of spectral minutiae representation. A correlation based spectral minutiae\ud matching algorithm is presented and evaluated. The scheme shows a promising result, with an equal error rate of 0.2% on manually extracted minutiae

Waveform considerations in space-variant optical processors

The use of coded waveforms in space-variant optical signal processors using coordinate transformations is considered. It is shown that nonlinear transmitted coded signals must be used with such a processor and that this results in novel waveform design and system approaches for radar and communications

Invariant recognition of polychromatic images of Vibrio cholerae O1

7 pages, 5 figures.-- ©2002 Society of Photo-Optical Instrumentation Engineers.Cholera is an acute intestinal infectious disease. It has claimed many lives throughout history, and it continues to be a global health threat. Cholera is considered one of the most important emergence diseases due its relation with global climate changes. Automated methods such as optical systems represent a new trend to make more accurate measurements of the presence and quantity of this microorganism in its natural environment. Automatic systems eliminate observer bias and reduce the analysis time.We evaluate the utility of coherent optical systems with invariant correlation for the recognition of Vibrio cholerae O1. Images of scenes are recorded with a CCD camera and decomposed in three RGB channels. A numeric simulation is developed to identify the bacteria in the different samples through an invariant correlation technique. There is no variation when we repeat the correlation and the variation between images correlation is minimum. The position-, scale-, and rotation-invariant recognition is made with a scale transform through the Mellin transform. The algorithm to recognize Vibrio cholerae O1 is the presence of correlation peaks in the green channel output and their absence in red and blue channels. The discrimination criterion is the presence of correlation peaks in red, green, and blue channels.Peer reviewe

Method of Synthesized Phase Objects in the Optical Pattern Recognition Problem

To solve the pattern recognition problem, a method of synthesized phase objects (SPO-method) is suggested. The essence of the suggested method is that synthesized phase objects are used instead of real amplitude objects. The former is object-dependent phase distributions calculated using the iterative Fourier transform algorithm. The method is experimentally studied with an optical-digital Vanderlugt and joint Fourier transform 4F-correlators. The development of the SPO-method for the rotation invariant pattern recognition is considered as well. We present the comparative analysis of recognition results with the use of the conventional and proposed methods, estimate the sensitivity of the latter to distortions of the structure of objects, and determine the applicability limits. It is demonstrated that the SPO-method allows one: (a) to simplify the procedure of choice of recognition signs (criteria); (b) to obtain one-type δ-like recognition signals irrespective of the type of objects; and (c) to improve the signal-to-noise ratio for correlation signals by 20–30 dB on the average. To introduce recognition objects in a correlator, we use SLM LC-R 2500 and SLM HEO 1080 Pluto devices

Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen