Melon Stem Image Analysis for Climacteric Ripeness Detection
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Solution Overview
Problem
It is difficult to determine the ripeness of melons accurately due to variations in climacteric ripening based on storage conditions, variety, and time of year, and external skin changes are not reliable indicators for ripeness.
Innovation Solution
A ripeness determination system and method using image processing to analyze the stem of a melon, incorporating a mount for image capture and preprocessing steps to extract and adjust the stem image, followed by tone and dimension calculations to determine climacteric ripeness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If external skin changes are used to determine ripeness, then the determination process is simple, but the accuracy is low due to variations in climacteric ripening
Solution Approach 1:
The patent extracts the stem from the melon as a separate indicator for ripeness determination. Instead of relying on external skin changes, the system captures and analyzes images of the stem, extracting features such as color tone (yellow/brown ratio) and dimensional changes (thickness, length) that correlate with climacteric ripening progress.
Solution Approach 2:
The patent monitors parameter changes in the stem as the melon ripens. Specifically, it tracks the change in color tone (increase in yellow/brown components) and dimensional parameters (decrease in thickness and length) of the stem, using these parameter transformations as indicators of ripeness degree.
2Measurement precision
If multiple factors from stem images are analyzed, then the ripeness determination accuracy is improved, but the processing complexity increases
Solution Approach 1:
The patent segments the stem image analysis into distinct feature extraction components: color tone analysis (calculating yellow and brown color ratios), dimensional analysis (measuring stem thickness and length), and shape analysis. This segmentation allows each aspect to be processed independently and combined for final determination.
Solution Approach 2:
The patent transforms the complex image data into simplified quantitative parameters. It calculates the ratio of yellow to brown color tones, measures dimensional changes in the stem, and converts these physical changes into a standardized ripeness degree score, making the processing more systematic and manageable.
3Reliability
If stem images are used instead of skin images, then reliable ripeness indicators are obtained, but the ease of operation decreases
Solution Approach 1:
The patent creates a digital copy (image) of the stem for analysis. Instead of physically examining the stem, the system captures an image of it and processes the digital representation, allowing for non-contact, automated analysis while maintaining the reliability of stem-based indicators.
Solution Approach 2:
The patent replaces manual mechanical inspection of the stem with an automated image processing system. The mechanical act of examining the stem is substituted by capturing an image and using computer vision algorithms to analyze stem characteristics, improving consistency and reliability.
Data Source
AI summary
A ripeness determination system and a ripeness determination method that include determining a degree of climacteric ripeness of a melon based on at least two factors obtained from an image of a stem of the melon, and determining whether the melon is ripe to eat based on the degree of climacteric ripeness.