Pattern recognition system invariant to rotation and scale to identify color images

Angel Coronel-Beltrán

doi:10.1063/1.4897703

Pattern recognition system invariant to rotation and scale to identify color images

^*Autor correspondiente de este trabajo

Departamento de Investigación en Física

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

This work presents a pattern recognition digital system based on nonlinear correlations. The correlation peak values given by the system were analyzed by the peak-to-correlation energy (PCE) metric to determine the optimal value of the non-linear coefficient kin the k-law. The system was tested with 18 different color images of butterflies; each image was rotated from 0° to 180° with increments of 1° and scaled ±25% with increments of 1% and to take advantage of the color property of the images the RGB model was employed. The boxplot statistical analysis of the mean with ±2∗EE (standard errors) for the PCE values set that the system invariant to rotation and scale has a confidence level at least of 95.4%.

Idioma original	Inglés
Título de la publicación alojada	International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014
Editores	Theodore E. Simos, Theodore E. Simos, Theodore E. Simos, Theodore E. Simos, Theodore E. Simos, Zacharoula Kalogiratou, Theodore Monovasilis
Editorial	American Institute of Physics Inc.
Páginas	151-154
Número de páginas	4
ISBN (versión digital)	9780735412552
DOI	https://doi.org/10.1063/1.4897703
Estado	Publicada - 6 oct. 2014
Evento	International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014 - Athens, Grecia Duración: 4 abr. 2014 → 7 abr. 2014

Serie de la publicación

Nombre	AIP Conference Proceedings
Volumen	1618
ISSN (versión impresa)	0094-243X
ISSN (versión digital)	1551-7616

Conferencia

Conferencia	International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014
País/Territorio	Grecia
Ciudad	Athens
Período	4/04/14 → 7/04/14

Nota bibliográfica

Publisher Copyright:
© 2014 AIP Publishing LLC.

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10.1063/1.4897703

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Coronel-Beltrán, A. (2014). Pattern recognition system invariant to rotation and scale to identify color images. En T. E. Simos, T. E. Simos, T. E. Simos, T. E. Simos, T. E. Simos, Z. Kalogiratou, & T. Monovasilis (Eds.), International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014 (pp. 151-154). (AIP Conference Proceedings; Vol. 1618). American Institute of Physics Inc.. https://doi.org/10.1063/1.4897703

Coronel-Beltrán, Angel. / Pattern recognition system invariant to rotation and scale to identify color images. International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014. editor / Theodore E. Simos ; Theodore E. Simos ; Theodore E. Simos ; Theodore E. Simos ; Theodore E. Simos ; Zacharoula Kalogiratou ; Theodore Monovasilis. American Institute of Physics Inc., 2014. pp. 151-154 (AIP Conference Proceedings).

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title = "Pattern recognition system invariant to rotation and scale to identify color images",

abstract = "This work presents a pattern recognition digital system based on nonlinear correlations. The correlation peak values given by the system were analyzed by the peak-to-correlation energy (PCE) metric to determine the optimal value of the non-linear coefficient kin the k-law. The system was tested with 18 different color images of butterflies; each image was rotated from 0° to 180° with increments of 1° and scaled ±25% with increments of 1% and to take advantage of the color property of the images the RGB model was employed. The boxplot statistical analysis of the mean with ±2∗EE (standard errors) for the PCE values set that the system invariant to rotation and scale has a confidence level at least of 95.4%.",

keywords = "Pattern recognition, color model, digital correlation, nonlinear filter",

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note = "Publisher Copyright: {\textcopyright} 2014 AIP Publishing LLC.; International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014 ; Conference date: 04-04-2014 Through 07-04-2014",

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Coronel-Beltrán, A 2014, Pattern recognition system invariant to rotation and scale to identify color images. En TE Simos, TE Simos, TE Simos, TE Simos, TE Simos, Z Kalogiratou & T Monovasilis (eds.), International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014. AIP Conference Proceedings, vol. 1618, American Institute of Physics Inc., pp. 151-154, International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014, Athens, Grecia, 4/04/14. https://doi.org/10.1063/1.4897703

Pattern recognition system invariant to rotation and scale to identify color images. / Coronel-Beltrán, Angel.
International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014. ed. / Theodore E. Simos; Theodore E. Simos; Theodore E. Simos; Theodore E. Simos; Theodore E. Simos; Zacharoula Kalogiratou; Theodore Monovasilis. American Institute of Physics Inc., 2014. p. 151-154 (AIP Conference Proceedings; Vol. 1618).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AB - This work presents a pattern recognition digital system based on nonlinear correlations. The correlation peak values given by the system were analyzed by the peak-to-correlation energy (PCE) metric to determine the optimal value of the non-linear coefficient kin the k-law. The system was tested with 18 different color images of butterflies; each image was rotated from 0° to 180° with increments of 1° and scaled ±25% with increments of 1% and to take advantage of the color property of the images the RGB model was employed. The boxplot statistical analysis of the mean with ±2∗EE (standard errors) for the PCE values set that the system invariant to rotation and scale has a confidence level at least of 95.4%.

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Coronel-Beltrán A. Pattern recognition system invariant to rotation and scale to identify color images. En Simos TE, Simos TE, Simos TE, Simos TE, Simos TE, Kalogiratou Z, Monovasilis T, editores, International Conference of Computational Methods in Sciences and Engineering 2014, ICCMSE 2014. American Institute of Physics Inc. 2014. p. 151-154. (AIP Conference Proceedings). doi: 10.1063/1.4897703

Pattern recognition system invariant to rotation and scale to identify color images

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