Proceedings of the 4th International Conference on Information Technology and Management Innovation

Research on Object Detection based on Mathematical Morphology

Authors
S. Qian, G.R. Weng
Corresponding Author
S. Qian
Available Online October 2015.
DOI
10.2991/icitmi-15.2015.36How to use a DOI?
Keywords
Object detection; Mathematical morphology; Image segmentation
Abstract

An approach for object detection based on mathematical morphology is proposed in this paper. The features of objects are extracted through the analysis of images, and structuring elements with different shapes and sizes are selected according to the aim of experiments. After the image preprocessing, a gray image is obtained, which is propitious to the analysis of computer. Then the image is used by a threshold and a binary image is achieved. At length, the objects are detected through mathematical morphology. Experimental results show that the proposed approach to object detection is feasible with Mathematical Morphology. And it has a great effect.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 4th International Conference on Information Technology and Management Innovation
Series
Advances in Computer Science Research
Publication Date
October 2015
ISBN
10.2991/icitmi-15.2015.36
ISSN
2352-538X
DOI
10.2991/icitmi-15.2015.36How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - S. Qian
AU  - G.R. Weng
PY  - 2015/10
DA  - 2015/10
TI  - Research on Object Detection based on Mathematical Morphology
BT  - Proceedings of the 4th International Conference on Information Technology and Management Innovation
PB  - Atlantis Press
SP  - 203
EP  - 208
SN  - 2352-538X
UR  - https://doi.org/10.2991/icitmi-15.2015.36
DO  - 10.2991/icitmi-15.2015.36
ID  - Qian2015/10
ER  -