Comparative Analysis between LDR and HDR Images for Automatic Fruit Recognition and Counting

Joint Authors

Coelho, João Paulo
Boaventura-Cunha, José
Pinho, Tatiana M.
Oliveira, Josenalde

Source

Journal of Sensors

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-08-03

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Civil Engineering

Abstract EN

Precision agriculture is gaining an increasing interest in the current farming paradigm.

This new production concept relies on the use of information technology (IT) to provide a control and supervising structure that can lead to better management policies.

In this framework, imaging techniques that provide visual information over the farming area play an important role in production status monitoring.

As such, accurate representation of the gathered production images is a major concern, especially if those images are used in detection and classification tasks.

Real scenes, observed in natural environment, present high dynamic ranges that cannot be represented by the common LDR (Low Dynamic Range) devices.

However, this issue can be handled by High Dynamic Range (HDR) images since they have the ability to store luminance information similarly to the human visual system.

In order to prove their advantage in image processing, a comparative analysis between LDR and HDR images, for fruits detection and counting, was carried out.

The obtained results show that the use of HDR images improves the detection performance to more than 30% when compared to LDR.

American Psychological Association (APA)

Pinho, Tatiana M.& Coelho, João Paulo& Oliveira, Josenalde& Boaventura-Cunha, José. 2017. Comparative Analysis between LDR and HDR Images for Automatic Fruit Recognition and Counting. Journal of Sensors،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1187312

Modern Language Association (MLA)

Pinho, Tatiana M.…[et al.]. Comparative Analysis between LDR and HDR Images for Automatic Fruit Recognition and Counting. Journal of Sensors No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1187312

American Medical Association (AMA)

Pinho, Tatiana M.& Coelho, João Paulo& Oliveira, Josenalde& Boaventura-Cunha, José. Comparative Analysis between LDR and HDR Images for Automatic Fruit Recognition and Counting. Journal of Sensors. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1187312

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1187312