Composite filters for search time reduction for 3D model based object recognition

Rahman, Mahbuba; Awwal, Abdul Ahad S.; Gudmundsson, Karl S.

doi:10.1117/12.508655

Cited by 5 publications

(5 citation statements)

References 3 publications

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“…We should notice that this conclusion is similar to that noted by Mohammed et al in [32]. The low performances of the binarized POF is confirmed by a comparison between the results obtained by Mohammed et al [32] and those reported by Rahman et al [31].…”

Section: Composite Filters Used For Comparison With the Aspofsupporting

confidence: 91%

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Spectral optimized asymmetric segmented phase-only correlation filter

2012

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We suggest a new type of optimized composite filter, i.e. the asymmetric segmented phase-only filter (ASPOF), for improving the effectiveness of a VanderLugt correlator (VLC) when used for face identification. Basically, it consists in merging several reference images after application of a specific spectral optimization method.After segmentation of the spectral filter plane to several areas, each area is assigned to a single winner reference according to a new optimized criterion. The point of the paper is to show that this method offers a significant performance improvement on standard composite filters for face identification. We first briefly revisit composite filters (adapted, phase-only, inverse, compromise optimal, segmented, minimum average correlation energy, optimal trade-off maximum average correlation, and amplitude modulated phase-only (AMPOF)) which are tools of choice for face recognition based on correlation techniques and compare their performances with those of the ASPOF. We illustrate some of the drawbacks of current filters for several binary and gray scale images identifications. Next, we describe the optimization steps and introduce the ASPOF that can overcome these technical issues to improve the quality and the reliability of the correlation based decision. We derive performance measures, i.e. peak-to-correlation energy values and receiver operating characteristic curves, to confirm consistency of the results. We numerically find that this filter increases the recognition rate and decrease the false alarm rate. The results show that the discrimination of the ASPOF is comparable to that of the AMPOF, but the ASPOF is more robust than the trade-off maximum average correlation height 3 (OT-MACH) against rotation and various types of noise sources. Our method has several features that make it amenable to experimental implementation using a VLC.4

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Section: Composite Filters Used For Comparison With the Aspofsupporting

confidence: 91%

“…It is important to point out that the PCE values obtained from the correlation of the letter V correlated with the same filters have an average value less than 10 -3 , and support the conclusions reported in [31].…”

Section: Composite Filters Used For Comparison With the Aspofsupporting

confidence: 84%

Spectral optimized asymmetric segmented phase-only correlation filter

2012

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“…One of the characteristics of the KDP back-reflection image is the presence of well-defined, relatively stable fringe patterns within the beam. We show in this paper that these fringe patterns facilitate a stable beam position detection method based on a composite [2] amplitude modulated phase only matched filter (AMPOF) [3].…”

Section: Introductionmentioning

confidence: 92%

“…Moving to an AMPOF performed further optimization on the composite CMF. Optimization was improved even further by developing a composite AMPOF filter [2,3] producing a radial standard deviation of only 0.27 pixels.…”

Section: Algorithm Testing and Modificationsmentioning

confidence: 99%

Composite amplitude-modulated phase-only filter-based detection and tracking of the back-reflection of KDP images

et al. 2004

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An algorithm for determining the position of the KDP back-reflection image was developed. It was compared to a centroid-based algorithm. While the algorithm based on centroiding exhibited a radial standard deviation of 9 pixels, the newly proposed algorithm based on classical matched filtering (CMF) and a Gaussian fit to correlation peak provided a radial standard deviation of less than 1 pixel. The speed of the peak detection was improved from an average of 5.5 seconds for Gaussian fit to 0.022 seconds by using a polynomial fit. The performance was enhanced even further by utilizing a composite amplitude modulated phase only filter; producing a radial standard deviation of 0.27 pixels. The proposed technique was evaluated on 900+ images with varying degrees of noise and image amplitude as well as real National Ignition Facility (NIF) images.

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“…The National Ignition Facility, currently under construction at the Lawrence Livermore National Laboratory, is a stadium-sized facility containing a 192-beam, 1.8-megajoule, 500-terawatt, ultraviolet laser system for the study of inertial confinement fusion and the physics of matter at extreme energy densities and pressures [1] . The FOA is the last element of the NIF main laser system and the first of the target area systems.…”

Section: Introductionmentioning

confidence: 99%

Optimization and improvement of FOA corner cube algorithm

et al. 2004

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Alignment of laser beams based on video images is a crucial task necessary to automate operation of the 192 beams at the National Ignition Facility (NIF). The final optics assembly (FOA) is the optical element that aligns the beam into the target chamber. This work presents an algorithm for determining the position of a corner cube alignment image in the final optics assembly. The improved algorithm was compared to the existing FOA algorithm on 900 noise-simulated images. While the existing FOA algorithm based on correlation with a synthetic template has a radial standard deviation of 1 pixel, the new algorithm based on classical matched filtering (CMF) and polynomial fit to the correlation peak improves the radial standard deviation performance to less than 0.3 pixels. In the new algorithm the templates are designed from real data stored during a year of actual operation.

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Composite filters for search time reduction for 3D model based object recognition

Cited by 5 publications

References 3 publications

Spectral optimized asymmetric segmented phase-only correlation filter

Spectral optimized asymmetric segmented phase-only correlation filter

Composite amplitude-modulated phase-only filter-based detection and tracking of the back-reflection of KDP images

Optimization and improvement of FOA corner cube algorithm

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