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Full-Text Articles in Engineering
Circular Optimal Trade-Off And Distance-Classifier Correlation Filters, Samuel Peter Kozaitis, Sila Thangwaritorn
Circular Optimal Trade-Off And Distance-Classifier Correlation Filters, Samuel Peter Kozaitis, Sila Thangwaritorn
Electrical Engineering and Computer Science Faculty Publications
We use circular versions of advanced distortion-invariant filters such as optimal trade-off synthetic discriminant function and distance classifier correlation filters to obtain rotation invariance with an optical correlator. The filter noise performance is compared using a common measure of probability of error because the filters have different characteristics. The filters are real-valued so they can be implemented on a variety of SLMs. The circular symmetry of the filters significantly decreases their computational requirement.
Design Of Distortion-Invariant Correlation Filters Using Supervised Learning, Samuel Peter Kozaitis, Rufus H. Cofer, Wesley E. Foor
Design Of Distortion-Invariant Correlation Filters Using Supervised Learning, Samuel Peter Kozaitis, Rufus H. Cofer, Wesley E. Foor
Electrical Engineering and Computer Science Faculty Publications
We designed binary phase-only filters from a training set of images using a statistical approach. We forced images into clusters and designed filters to recognize objects from that cluster. We report on results obtained by computer simulation comparing the performance of filters to recognize objects from clusters of one and two classes.
Feature-Based Correlation Filters For Distortion Invariance, Samuel Peter Kozaitis, Robert Petrilak, Wesley E. Foor
Feature-Based Correlation Filters For Distortion Invariance, Samuel Peter Kozaitis, Robert Petrilak, Wesley E. Foor
Electrical Engineering and Computer Science Faculty Publications
In an optical correlator, binary phase-only filters (BPOFs) that recognize objects that vary in a nonrepeatable way are essential for recognizing objects from actual sensors. An approach is required that is as descriptive as a BPOF yet robust to object and background variations of an unknown or nonrepeatable type. We developed a BPOF that was more robust than a synthetic discriminant function (SDF) filter. This was done by creating a filter that retained the invariant features of a training set. By simulation, our feature-based filter offered a range of performance by setting a parameter to different values. As the value …
Multiresolution Template Matching Using An Optical Correlator, Samuel Peter Kozaitis, Zia Saquib, Rufus H. Cofer, Wesley E. Foor
Multiresolution Template Matching Using An Optical Correlator, Samuel Peter Kozaitis, Zia Saquib, Rufus H. Cofer, Wesley E. Foor
Electrical Engineering and Computer Science Faculty Publications
Infrared imagery of 512 × 512 pixels was processed with 128 × 128 arrays by computer simulation of an optical correlator using various correlation filters. Pyramidal processing using binary phase-only filters (BPOFs), synthetic discriminant function (SDF) filters, and feature-based filters was used to process an entire image in parallel at different resolutions. Results showed that both SDF and feature-based filters were more robust to the effects of thresholding input imagery than BPOFs. The feature-based filters offered a range of performance by setting a parameter to different values. As the value of the parameter was changed, correlation peaks within the training …