ICM image separation based available parking space detection

Authors

  • Víctor Romero Bautista Benemérita Universidad Autónoma de Puebla
  • Aldrin Barreto Flores Benemérita Universidad Autónoma de Puebla
  • Salvador E. Ayala Raggi Benemérita Universidad Autónoma de Puebla
  • Verónica E. Bautista López Benemérita Universidad Autónoma de Puebla

Keywords:

Classification, feature extraction, Parking Space

Abstract

Parking lot systems based on computer vision have been used frequently in recent years to improve vehicle traffic on urban areas. These systems provide information about the availability of a parking place, furthermore these systems contribute for a better organization and to reduce the time to looking for a free space. One of the main challenges for these systems is the occlusion effects that occur frequently due to the location of the cameras in the parking lots. In this paper, we present a method for available parking place detection, where we contribute with a mechanism to reduce occlusion effects that consists of feature extraction using ICM based on input image separation. The results shows that our contribution significantly reduces the noise generated by occlusion effects. The proposed method was evaluated by our dataset and an external dataset, where the experiments results achieving up 0.98 accuracy.

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Published

2023-03-01

How to Cite

Romero Bautista, V. ., Barreto Flores, A., Ayala Raggi, S. E., & Bautista López, V. E. (2023). ICM image separation based available parking space detection. International Journal of Combinatorial Optimization Problems and Informatics, 14(1), 49–65. Retrieved from https://ijcopi.org/ojs/article/view/343

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