Fruit sweetness analysis system

Abstract

This invention discloses a fruit sweetness analysis system, comprising: an image capturing module configured to capture an image of a fruit; a color feature generation module configured to obtain a combination of color features from the image combining one of multiple color spaces; a classification device configured to classify the sweetness level of the fruit based on the color feature combination; and a processor connected to the image capturing module, the color feature generation module, and the classification device, and configured to control the operation of the image capturing module, the color feature generation module, and the classification device. This fruit sweetness analysis system can determine the sweetness of fruit in a non-destructive manner and improve the accuracy of sweetness classification.

Claims

1. A fruit sweetness analysis system, comprising: an image capturing device configured to capture an image of a fruit; a color feature generating device configured to obtain a combination of color features from one of a plurality of color spaces from the image of the fruit; a classification device configured to classify the sweetness level of the fruit based on the combination of color features; and a processor connected to the image capturing device, the color feature generating device, and the classification device, and configured to control the operation of the image capturing device, the color feature generating device, and the classification device.

2. The fruit sweetness analysis system as described in claim 1, wherein, This combination of color features includes multiple color features derived from the plurality of color spaces.

3. The fruit sweetness analysis system as described in claim 1, wherein, One of the feature values ​​in this color feature combination contains a channel that is sensitive to the red hue or red content of the fruit.

4. The fruit sweetness analysis system as described in claim 1, wherein, The plurality of color spaces are selected from the group consisting of the RGB color space, the HSV color space, the Lab color space, and combinations thereof.

5. The fruit sweetness analysis system as described in claim 1, wherein, The classification device includes a machine learning classifier.

6. The fruit sweetness analysis system as described in claim 5, wherein, The machine learning classifier is selected from a group consisting of K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Random Forest, and combinations thereof.

7. The fruit sweetness analysis system as described in claim 1, wherein, The classification device is configured to output a binary classification result for the sweetness of the fruit.

8. The fruit sweetness analysis system as described in claim 1 further includes a background processing device connected to and controlled by the processor, the background processing device being configured to remove a background from the image of the fruit.

9. The fruit sweetness analysis system as described in claim 8, wherein, The background processing device is configured to extract a region of interest from the image representing the appearance of the fruit.

10. The fruit sweetness analysis system as described in claim 1 further includes a model update device connected to and controlled by the processor, the model update device being configured to update the classification device based on an image of a newly added fruit and its corresponding sweetness information.

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