A
system for the automated evaluation of tobacco leaves, comprising: • a mechanical feeding module (201) configured to feed individual tobacco leaves one after the other; • a controlled imaging chamber (202) equipped with a high-resolution camera and calibrated light sources to capture detailed images of tobacco leaves under standardized lighting conditions; • a
color sensor (203) configured to extract colorimetric data from the tobacco leaves, including, but not limited to, RGB values and
hue information; • a
processing unit (204) comprising one or more processors and memories configured to: i) performing image pre-
processing including
noise reduction and
contrast enhancement, (ii) Execution of segmentation algorithms to isolate the leaf from the background, (iii) Extraction of visual features such as size, shape, texture and color uniformity from the images, (iv) Analyzing the sensor data using statistical or
machine learning models to determine quality parameters, (v) Integration of the extracted image features and colorimetric data into an
evaluation algorithm based on predefined quality standards, (vi) to assign a quality mark to each
tobacco leaf on the basis of the analysis; • an output module (205) configured to display the
classification result in real time via an LED screen or a
digital interface; • a storage module (206) configured to store classification results for future reference and analysis; • and an
Internet of Things (IoT) communication module (207) that enables remote access,
monitoring and control of the classification process.