Scalpel Region Detection based on the Location of Color Marks and Edge Detection

Juan Carlos Suarez-Quispe; Oscar E. Ramos

doi:10.1109/INTERCON50315.2020.9220207

Scalpel Region Detection based on the Location of Color Marks and Edge Detection

Juan Carlos Suarez-Quispe, Oscar E. Ramos

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

1 Cita (Scopus)

Resumen

This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781728193779
DOI	https://doi.org/10.1109/INTERCON50315.2020.9220207
Estado	Publicada - set. 2020
Publicado de forma externa	Sí
Evento	27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 - Virtual, Lima, Perú Duración: 3 set. 2020 → 5 set. 2020

Serie de la publicación

Nombre	Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020

Conferencia

Conferencia	27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
País/Territorio	Perú
Ciudad	Virtual, Lima
Período	3/09/20 → 5/09/20

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10.1109/INTERCON50315.2020.9220207

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Suarez-Quispe, J. C., & Ramos, O. E. (2020). Scalpel Region Detection based on the Location of Color Marks and Edge Detection. En Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 Artículo 9220207 (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INTERCON50315.2020.9220207

Suarez-Quispe, Juan Carlos ; Ramos, Oscar E. / Scalpel Region Detection based on the Location of Color Marks and Edge Detection. Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020).

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title = "Scalpel Region Detection based on the Location of Color Marks and Edge Detection",

abstract = "This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed.",

keywords = "Color Thresholds, Digital Image Processing, Edge Detection, Fuzzy Logic",

author = "Suarez-Quispe, {Juan Carlos} and Ramos, {Oscar E.}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 ; Conference date: 03-09-2020 Through 05-09-2020",

year = "2020",

month = sep,

doi = "10.1109/INTERCON50315.2020.9220207",

language = "English",

series = "Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020",

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Suarez-Quispe, JC & Ramos, OE 2020, Scalpel Region Detection based on the Location of Color Marks and Edge Detection. En Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020., 9220207, Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020, Institute of Electrical and Electronics Engineers Inc., 27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020, Virtual, Lima, Perú, 3/09/20. https://doi.org/10.1109/INTERCON50315.2020.9220207

Scalpel Region Detection based on the Location of Color Marks and Edge Detection. / Suarez-Quispe, Juan Carlos; Ramos, Oscar E.
Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9220207 (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020).

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

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T1 - Scalpel Region Detection based on the Location of Color Marks and Edge Detection

AU - Suarez-Quispe, Juan Carlos

AU - Ramos, Oscar E.

PY - 2020/9

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N2 - This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed.

AB - This work proposes an algorithm for scalpel region detection using color segmentation and edge detection. The input images are obtained with a fixed camera that has a line of view perpendicular to the scalpel plane. Three squares of red, green and blue colors were added to the scalpel in order to serve as fiducials. For the detection of those marks, the use of two methods was evaluated: One based on the application of thresholds to the color components, and the other based on the use of a fuzzy rule machine. The experimentation shows that both approaches provide similar results. Some morphological operations are then applied in order to detect the scalpel region. The algorithm was successfully tested in several cases, and some examples of the results are presented and analyzed.

KW - Color Thresholds

KW - Digital Image Processing

KW - Edge Detection

KW - Fuzzy Logic

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M3 - Conference contribution

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Suarez-Quispe JC, Ramos OE. Scalpel Region Detection based on the Location of Color Marks and Edge Detection. En Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9220207. (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020). doi: 10.1109/INTERCON50315.2020.9220207

Scalpel Region Detection based on the Location of Color Marks and Edge Detection

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