A Mobile Application for Direct Light Compensation in Smartphone-Based Fruit Image Acquisition Systems.

Area of Science:

• Agricultural Science
• Computer Vision
• Spectroscopy

Background:

• Estimating bergamot essential oil content requires standardized image acquisition.
• Previous methods used bulky dark boxes, limiting field applicability.
• Environmental variables like sunlight and shadows affect image quality.

Purpose of the Study:

• To develop a versatile smartphone-based mobile application for in situ image color calibration.
• To replace physical shielding with digital compensation for accurate colorimetric sensing.
• To enable real-time image correction regardless of orchard lighting conditions.

Main Methods:

• A mobile application was developed using a color card reference for calibration.
• ArUco Markers were utilized for autonomous detection of the color card and fruit surface.
• An RGB histogram matching algorithm performed dynamic chromatic transformation for image normalization.

Main Results:

• The application successfully performed automated color calibration using a mobile colorimetric sensor.
• Normalized, high-fidelity images were generated, suitable for chromatic index calculation.
• Results showed good agreement with traditional inspection chamber methods.

Conclusions:

• The mobile application is a valid and reliable tool for color calibration in field conditions.
• It offers a versatile alternative to traditional inspection chambers for image acquisition.
• The app enables accurate estimation of essential oil content, independent of environmental lighting.