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

المؤلفون المشاركون

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

المصدر

Journal of Sensors

العدد

المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-12، 12ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2017-08-03

دولة النشر

مصر

عدد الصفحات

12

التخصصات الرئيسية

هندسة مدنية

الملخص 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.

نمط استشهاد جمعية علماء النفس الأمريكية (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

نمط استشهاد الجمعية الأمريكية للغات الحديثة (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

نمط استشهاد الجمعية الطبية الأمريكية (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

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1187312