IDENTIFICATION OF MULTIPLE OVERLAPPING OBJECTS: DESCRIPTIVE STATISTICS

Abstract

The recognition of objects in an instantaneous image is an area of research that has been explored over several decades, in which there are extraordinary achievements and advances. However, problems persist that have not been clearly overcome by the world scientific community, such as the separation of overlapping digital objects. This article briefly describes the descriptive measures of centralization of data applied in the identification of irregularly shaped digital
objects generated by overlapping objects; as a prior knowledge to continue future investigations.

Keywords: Generational diversity; sustainability; family company.

REFERENCES

[1] A. Bohm, M. Tatarchenko and T. Falk. Se­mantic instance segmentation of touching and overlap­ping objects. Department of Computer Science, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany. 2018.

[2] Z. Lu, G. Carneiro and A. Bradley. Automa­ted nucleus and cytoplasm segmentation of overlapping cervical cells. Department of Computer Science, City University of Hong Kong, China. 2013.

[3] S. Alayón, S. Sánchez, J. Sigut and J. Méndez. Segmentación automática de núcleos solapados en imá­genes de citologías. Universidad de La Laguna, España. 2013.

[4] A. Borrero,  J. Maldonado, and  E. Lobo. Selección de una técnica robusta de extracción de ca­racterísticas para identificar condiciones físicas de las briquetas de hierro producidas en la empresa Orinoco Iron, S.C.S., Universidad de los Andes, Facultad de In­geniería, Mérida, Venezuela. 2012.

[5] S. Zulma. Caracterización y clasificación de café cereza usando visión artificial, Magister en Auto­matización Industrial, Universidad Nacional de Colom­bia, Sede Manizales.

[6]Fujiyoshi H. y Kanade, T. (2004). Layered detection for multiple overlapping objects. IEICE TRANS. INF. & SYST., VOL. E87-D, NO.12 December. 2005.