Enhancing the Repeatability Quality of Feature Detector in Epipolar Geometry

Palabras clave: Epipolar Geometry, Feature Detector, Keypoint, Repeatability Quality. Calidad de repetibilidad, Detector de características, Geometría epipolar, Punto clave.

Resumen

ABSTRACT

 

This study discusses evaluating the repeatability quality of feature detector algorithms for image key points in epipolar geometry. Although no one has been able to examine performance in this area; hence, the necessity of conducting research based on improvement. In our method, the image format is converted into YCbCr, using only the Y channel, which is then tested with a variety of threshold values, and Weiner algorithm was applied as noise removal. Therefore, to prove the effectiveness, a comparison is made with the test results before and after method implementation, thus, verifying the success of the technique applied.

RESUMEN

 

Este estudio analiza la evaluación de la calidad de repetibilidad de los algoritmos de detección de características para puntos clave de imagen en geometría epipolar. Aunque nadie ha podido examinar el desempeño en esta área; de ahí la necesidad de realizar investigaciones basadas en la mejora. En nuestro método, el formato de imagen se convierte en YCbCr, utilizando solo el canal Y, que luego se prueba con una variedad de valores umbral, y se aplicó el algoritmo Weiner como eliminación de ruido. Por lo tanto, para probar la efectividad, se realiza una comparación con los resultados de la prueba antes y después de la implementación del método, verificando así el éxito de la técnica aplicada.

Biografía del autor/a

A. KUSNADI, Universitas Multimedia Nusantara

Adhi started bachelor's degree in 1991. Then in 2005, continued formal master's education at IPB, Indonesia, in the field of Computer Engineering. Currently working as an Informatic lecturer at Universitas Multimedia Nusantara, Indonesia. While being a lecturer, he has produced several publications. Published research topics include Classification and Image processing. His areas of interest are software engineering, information system development, data analytics, and artificial intelligence.

W. S. KOM, Universitas Multimedia Nusantara

Wella started his bachelor's degree in 2009, in the field of Information Systems at Multimedia Nusantara University, Indonesia. Then in 2014, he continued his formal master's education at Bina Nusantara University, Indonesia, in the field of Information Systems Management. She is currently working as an Information Systems lecturer at Multimedia Nusantara University, Indonesia, starting from 2015 until now. When he was a lecturer, he produced several publications. Published research topics include IT Governance, Behavior, Classification, and Image Processing. Currently, she is active as a member of the ISACA Academic Advocate Faculty Advisor and managing the ISACA Student Group Universitas Multimedia Nusantara.

R. WINANTYO, Universitas Multimedia Nusantara

Rangga, was born in Indonesia in 1980. He received the B.C.S. degree in information technology from the Royal Melbourne Institute of Technology, Australia, in 2004, the M.Sc. degree in new media technology from from International School of New Media, Luebeck, Germany in 2009, the Ph.D. degree in advanced material engineering from the Shizuoka University, Japan, in 2014, and Ph.D. degree in electrical engineering from the Universitas Indonesia, Indonesia, in 2015. He is currently a Senior Lecturer at the Universitas Multimedia Nusantara. His main areas of research interest are augmented reality, renewable energy, and advanced material. Dr. Winantyo is first person who receives two Ph.D. degree in Indonesia.

I. ZUHDI PANE, Universitas Multimedia Nusantara

Ivransa received Doctor of Engineering (in Electronics) from Graduate School of Information Science and Electrical Engineering, Kyushu University, Japan. He is presently working as senior lecturer in Department of Informatics, Multimedia Nusantara University, Indonesia. His areas of interest are software engineering, information system development, data analytics, and artificial intelligence.

Citas

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Publicado
2019-12-08
Cómo citar
KUSNADI, A., KOM, W. S., WINANTYO, R., & ZUHDI PANE, I. (2019). Enhancing the Repeatability Quality of Feature Detector in Epipolar Geometry. Utopía Y Praxis Latinoamericana, 24(1), 370-378. Recuperado a partir de https://produccioncientificaluz.org/index.php/utopia/article/view/29971