Efficient numerical analysis of optical imaging data: A comparative study |
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| Authors: | David Duarte-Correa,Alberto Pastrana-Palma,Carlos A. Olvera-Olvera,Sergio R. Ramí rez-Rodrí guez,Daniel Alaniz-Lumbreras,Domingo Gó mez-Melé ndez,Ismael de la Rosa,Salvador Noriega,Vianey Torres,Victor M. Castañ o |
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| Affiliation: | 1. Universidad Autónoma de Querétaro, Cerro de las Campanas s/n, 76010 Querétaro, Mexico;2. Unidad Académica de Ingeniería Eléctrica, Doctorado en Ingeniería Universidad Autónoma de Zacatecas, Jardín Juárez 146, Centro Histórico, Zacatecas, Mexico;3. Tlachia Systems S.A. de C.V., Calle 13 de septiembre No.1, Niños Héroes, C.P. 76010 Querétaro, Mexico;4. Universidad Politécnica de Querétaro, Carretera Estatal 420 S/N, El Rosario, C.P. 76240 El Marqués, Querétaro, Mexico;5. Departamento de Ingeniería Industrial y Manufactura, IIT, Universidad Autónoma de Ciudad Juárez, Av. P.E. Calles 1210, Fovissste Chamizal, C.P. 32310 Juárez, Chihuahua, Mexico |
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| Abstract: | The computational efficiency of 14 optical detectors over six types of transformations, namely: blur, illumination, rotation, viewpoint, zoom, and zoom-rotation changes, was analyzed. Images with the same resolution (750 × 500 pixels) were studied, in terms of correspondences, repeatability and computing time, and the correspondence was measured by using homographies i.e. projective transformations, to obtain the best efficiency for imaging applications. Results show that the multi-scale Harris Hessian detector is the most efficient for blur, illumination, and zoom-rotation changes. Meanwhile, multi-scale Hessian and Hessian Laplace are the best methods for rotation, viewpoint, and zoom changes. |
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| Keywords: | Interest points Detector Computing time |
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