The Experts below are selected from a list of 23652 Experts worldwide ranked by ideXlab platform
T B Britton - One of the best experts on this subject based on the ideXlab platform.
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indexing electron backscatter diffraction patterns with a refined Template Matching approach
Ultramicroscopy, 2019Co-Authors: Alexander Foden, David M Collins, A J Wilkinson, T B BrittonAbstract:Abstract Electron backscatter diffraction (EBSD) is a well-established method of characterisation for crystalline materials. Using this technique, we can rapidly acquire and index diffraction patterns to provide phase and orientation information about the crystals on the material surface. The conventional analysis method uses signal processing based on a Hough/Radon transform to index each diffraction pattern. This method is limited to the analysis of simple geometric features and ignores subtle characteristics of diffraction patterns, such as variations in relative band intensities. A second method, developed to address the shortcomings of the Hough/Radon transform, is based on Template Matching of a test experimental pattern with a large library of potential patterns. In the present work, the Template Matching approach has been refined with a new cross correlation function that allows for a smaller library and enables a dramatic speed up in pattern indexing. Refinement of the indexed orientation is performed with a follow-up step to allow for small alterations to the best match from the library search. The refined Template Matching approach is shown to be comparable in accuracy, precision and sensitivity to the Hough based method, even exceeding it in some cases, via the use of simulations and experimental data collected from a silicon single crystal and a deformed α-iron sample. The speed up and pattern refinement approaches should increase the widespread utility of pattern Matching approaches.
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indexing electron backscatter diffraction patterns with a refined Template Matching approach
arXiv: Materials Science, 2018Co-Authors: Alexander Foden, David M Collins, A J Wilkinson, T B BrittonAbstract:Electron backscatter diffraction (EBSD) is a well-established method of characterisation for crystalline materials. This technique can rapidly acquire and index diffraction patterns to provide phase and orientation information about the crystals on the material surface. The conventional analysis method uses signal processing based on a Hough/Radon transform to index each diffraction pattern. This method is limited to the analysis of simple geometric features and ignores subtle characteristics of diffraction patterns, such as variations in relative band intensities. A second method, developed to address the shortcomings of the Hough/Radon transform, is based on Template Matching of a test experimental pattern with a large library of potential patterns. In the present work, the Template Matching approach has been refined with a new cross correlation function that allows for a smaller library and enables a dramatic speed up in pattern indexing. Refinement of the indexed orientation is performed with a follow-up step to allow for small alterations to the best match from the library search. The orientation is further refined with rapid measurement of misorientation using whole pattern Matching. The refined Template Matching approach is shown to be comparable in accuracy, precision and sensitivity to the Hough based method, even exceeding it in some cases, via the use of simulations and experimental data collected from a silicon single crystal and a deformed {\alpha}-iron sample. The drastic speed up and pattern refinement approaches should increase the widespread utility of pattern Matching approaches.
David M Collins - One of the best experts on this subject based on the ideXlab platform.
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indexing electron backscatter diffraction patterns with a refined Template Matching approach
Ultramicroscopy, 2019Co-Authors: Alexander Foden, David M Collins, A J Wilkinson, T B BrittonAbstract:Abstract Electron backscatter diffraction (EBSD) is a well-established method of characterisation for crystalline materials. Using this technique, we can rapidly acquire and index diffraction patterns to provide phase and orientation information about the crystals on the material surface. The conventional analysis method uses signal processing based on a Hough/Radon transform to index each diffraction pattern. This method is limited to the analysis of simple geometric features and ignores subtle characteristics of diffraction patterns, such as variations in relative band intensities. A second method, developed to address the shortcomings of the Hough/Radon transform, is based on Template Matching of a test experimental pattern with a large library of potential patterns. In the present work, the Template Matching approach has been refined with a new cross correlation function that allows for a smaller library and enables a dramatic speed up in pattern indexing. Refinement of the indexed orientation is performed with a follow-up step to allow for small alterations to the best match from the library search. The refined Template Matching approach is shown to be comparable in accuracy, precision and sensitivity to the Hough based method, even exceeding it in some cases, via the use of simulations and experimental data collected from a silicon single crystal and a deformed α-iron sample. The speed up and pattern refinement approaches should increase the widespread utility of pattern Matching approaches.
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indexing electron backscatter diffraction patterns with a refined Template Matching approach
arXiv: Materials Science, 2018Co-Authors: Alexander Foden, David M Collins, A J Wilkinson, T B BrittonAbstract:Electron backscatter diffraction (EBSD) is a well-established method of characterisation for crystalline materials. This technique can rapidly acquire and index diffraction patterns to provide phase and orientation information about the crystals on the material surface. The conventional analysis method uses signal processing based on a Hough/Radon transform to index each diffraction pattern. This method is limited to the analysis of simple geometric features and ignores subtle characteristics of diffraction patterns, such as variations in relative band intensities. A second method, developed to address the shortcomings of the Hough/Radon transform, is based on Template Matching of a test experimental pattern with a large library of potential patterns. In the present work, the Template Matching approach has been refined with a new cross correlation function that allows for a smaller library and enables a dramatic speed up in pattern indexing. Refinement of the indexed orientation is performed with a follow-up step to allow for small alterations to the best match from the library search. The orientation is further refined with rapid measurement of misorientation using whole pattern Matching. The refined Template Matching approach is shown to be comparable in accuracy, precision and sensitivity to the Hough based method, even exceeding it in some cases, via the use of simulations and experimental data collected from a silicon single crystal and a deformed {\alpha}-iron sample. The drastic speed up and pattern refinement approaches should increase the widespread utility of pattern Matching approaches.
Mentari, Adhatil Putri - One of the best experts on this subject based on the ideXlab platform.
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RANCANG BANGUN ALAT DETEKSI UANG KERTAS PALSU DENGAN METODE Template Matching MENGGUNAKAN RASPBERRY PI
2015Co-Authors: Mentari, Adhatil PutriAbstract:Pada penelitian ini dirancang sebuah alat yang dapat mengidentifikasi keaslian uang kertas tanpa mengandalkan penglihatan manusia. Sistem pada alat ini menggunakan mini PC Raspberry Pi, lampu ultraviolet dan kamera dengan metode Template Matching. Template Matching adalah sebuah teknik pada pengolahan citra digital untuk menemukan bagian-bagian kecil dari gambar yang cocok dengan gambar Template. Lampu ultraviolet digunakan untuk memunculkan gambar Invisible Ink dari objek uang kertas pecahan 50.000. Kamera digunakan untuk menangkap gambar uang kertas setelah disinari lampu ultraviolet. Gambar tersebut kemudian diproses di raspberry pi menggunakan library opencv untuk mendapatkan nilai hasil kemiripan dengan gambar. Keluaran dari sistem ini berupa suara yang memberikan informasi tentang asli atau tidaknya uang kertas tersebut. Dari 16 kali percobaan dengan posisi kamera tetap dan berjarak + 8 cm dari uang, terdapat 2 kali kegagalan yang disebabkan tipisnya perbedaan warna dasar uang dengan gambar Template. Jadi didapatkan tingkat keberhasilan sebesar 87,5%. Sedangkan pada jarak + 7 cm dan +6 cm dari uang kertas sistem tidak dapat mendeteksi keaslian uang kertas tersebut. Dari 25 kali percobaan berdasarkan posisi/kemiringan uang kertas didapatkan tingkat 36%. Oleh karena itu Template Matching sangat dipengaruhi oleh Template ,thresholding ,posisi objek ,serta posisi/jarak kamera. Kata kunci : kamera , ultraviolet, Template Matching , raspberry pi , openc
Derisma D. - One of the best experts on this subject based on the ideXlab platform.
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Rancang Bangun Alat Deteksi Uang Kertas Palsu dengan Metode Template Matching Menggunakan Raspberry Pi
'Faculty of Islamic Studies - University of Muhammadiyah Jakarta', 2015Co-Authors: Putri M. A., Hendrick H., Erlina T., Derisma D.Abstract:Cara manual yang digunakan untuk mendeteksi keaslian uang kertas memiliki banyak kelemahan. Oleh karena itu, pada penelitian ini dirancang sebuah alat yang dapat mengidentifikasi keaslian uang kertas tanpa mengandalkan penglihatan manusia. Sistem pada alat ini menggunakan mini PC Raspberry Pi, lampu ultraviolet, kamera dan metode Template Matching. Template Matching adalah sebuah teknik pada pengolahan citra digital untuk menemukan bagian-bagian kecil dari gambar yang cocok dengan gambar Template. Lampu ultraviolet digunakan untuk memunculkan gambar Invisible Ink dari objek uang kertas pecahan 50.000. Kamera digunakan untuk menangkap gambar uang kertas setelah disinari lampu ultraviolet. Gambar tersebut kemudian diproses di Raspberry Pi menggunakan library OpenCV untuk mendapatkan nilai hasil kemiripan dengan gambar. Keluaran dari sistem ini berupa suara yang memberikan informasi tentang asli atau tidaknya uang kertas tersebut. Dari 16 kali percobaan dengan posisi kamera tetap dan berjarak + 8 cm dari uang, terdapat 2 kali kegagalan yang disebabkan tipisnya perbedaan warna dasar uang dengan gambar Template, sehingga didapatkan tingkat keberhasilan sebesar 87,5%. Sedangkan pada jarak + 7 cm dan +6 cm dari uang kertas sistem tidak dapat mendeteksi keaslian uang kertas tersebut. Dari 25 kali percobaan berdasarkan posisi/kemiringan uang kertas didapatkan tingkat 36%. Oleh karena itu Template Matching sangat dipengaruhi oleh Template, tresholding, posisi objek, serta posisi/jarak kamera
Keven J Laboyjuarez - One of the best experts on this subject based on the ideXlab platform.
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a normalized Template Matching method for improving spike detection in extracellular voltage recordings
Scientific Reports, 2019Co-Authors: Keven J Laboyjuarez, Seoiyoung Ahn, Daniel E FeldmanAbstract:Spike sorting is the process of detecting and clustering action potential waveforms of putative single neurons from extracellular voltage recordings. Typically, spike detection uses a fixed voltage threshold and shadow period, but this approach often misses spikes during high firing rate epochs or noisy conditions. We developed a simple, data-driven spike detection method using a scaled form of Template Matching, based on the sliding cosine similarity between the extracellular voltage signal and mean spike waveforms of candidate single units. Performance was tested in whisker somatosensory cortex (S1) of anesthetized mice in vivo. The method consistently detected whisker-evoked spikes that were missed by the standard fixed threshold. Detection was improved most for spikes evoked by strong stimuli (40-70% increase), improved less for weaker stimuli, and unchanged for spontaneous spiking. This represents improved detection during spatiotemporally dense spiking, and yielded sharper sensory tuning estimates. We also benchmarked performance using computationally generated voltage data. Template Matching detected ~85-90% of spikes compared to ~70% for the standard fixed threshold method, and was more tolerant to high firing rates and simulated recording noise. Thus, a simple Template Matching approach substantially improves detection of single-unit spiking for cortical physiology.
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a normalized Template Matching method for improving spike detection in extracellular voltage recordings
bioRxiv, 2018Co-Authors: Keven J Laboyjuarez, Seoiyoung Ahn, Daniel E FeldmanAbstract:Spike sorting is the process of detecting and clustering action potential waveforms from extracellular voltage recordings to identify spikes of putative single neurons. Typically, spike detection is done using a fixed voltage threshold and shadow period, but this approach can lead to missed spikes during high firing rate epochs or noisy conditions. We developed a novel spike detection method utilizing a computationally simple form of Template Matching that efficiently detects spikes from candidate single units and is tolerant of high firing rates and electrical noise without a whitening filter. Template Matching was based on a sliding cosine similarity between mean spike waveforms of candidate single units and the extracellular voltage signal. Performance was tested in whisker somatosensory cortex (S1) of anesthetized mice in vivo. The method consistently detected whisker-evoked spikes that were missed by a standard fixed voltage threshold. Detection was most improved for spikes evoked by strong stimuli (40-70% increase), less improved for weaker stimuli, and unchanged for spontaneous spiking. This reflected the failure of standard detection during spatiotemporally dense spiking. Template-based detection revealed higher signal-to-noise ratio for sensory responses and sharper sensory tuning. Thus, this Template Matching method (and other model-based spike detection methods) critically improve the quantification of single-unit spiking activity.
