Validation of an oil-palm detection system based on a logistic regression model

Claudia Rueda, Jhany Miserque, Rubbermaid Laverde

    Producción científica: Capítulo del libro/informe/acta de congresoPonencia publicada en las memorias del evento con ISBNrevisión exhaustiva

    3 Citas (Scopus)


    Oil palm plantations cover large areas. One of the main problems is to get an updated census of plants contained in these fields. Nowadays this process is done manually generating subjective results of the number of plants and so economic losses. This paper presents the validation of an oil palm detection and counting system. It uses a logistic regression model to classify images acquired by an unmanned aerial vehicle. First, the photogrammetry software processes acquired images to create orthomosaics. Then, the developed computer vision algorithm analyzes them. It uses a sliding window technique in image pyramids to generate candidates, an LBP descriptor to mathematically model image texture and a logistic regression model to classify windows. Finally, it applies a non-maximum suppression algorithm to enhance the decision. The system was validated using different images to those used in the training process. This process allowed us to determine how each parameter affects the system behavior. Also, it was possible to conclude that the most relevant parameters to improve system performance were the median filter and the size of sliding windows. The final system was assessed with images of real plantations obtaining a detection error of 4.66 percent and an F1 score of 0.97.

    Idioma originalInglés
    Título de la publicación alojadaProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016
    EditorialInstitute of Electrical and Electronics Engineers Inc.
    ISBN (versión digital)9781509025312
    EstadoPublicada - 27 ene. 2017
    Evento2016 IEEE ANDESCON, ANDESCON 2016 - Arequipa, Perú
    Duración: 19 oct. 201621 oct. 2016

    Serie de la publicación

    NombreProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016


    Conferencia2016 IEEE ANDESCON, ANDESCON 2016

    Nota bibliográfica

    Publisher Copyright:
    © 2016 IEEE.


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