Egg Shape Feature Extraction for Quality Assessment

In agricultural automation inspection, assessing the external quality of eggs is particularly crucial, especially for detecting surface cracks. Using MATLAB for egg shape feature extraction enables effective identification of shape characteristics in cracked regions, thereby determining egg integrity.

### Basic Approach Image Preprocessing Original egg images may suffer from uneven illumination or background interference. The process begins with grayscale conversion, followed by Gaussian filtering or median filtering to remove noise. Edge detection algorithms (such as the Canny operator) extract the egg contour, while morphological operations (like closing) fill minor breaks to ensure contour completeness.

Crack Region Localization After extracting the egg contour, threshold segmentation (e.g., Otsu's algorithm) distinguishes cracks from normal shell regions. Cracks typically manifest as local irregular shapes. Connected component analysis (using functions like `regionprops`) calculates features such as area, perimeter, and aspect ratio of crack regions.

Shape Feature Extraction For detected crack regions, multiple shape descriptors can be extracted, including: - Area: Number of pixels occupied by the crack. - Perimeter: Length of the closed contour along the crack edges. - Circularity: Measure of how closely the crack shape resembles a circle, calculated as (4π × Area / Perimeter²). - Convexity Defects: Maximum distance between the crack region and its convex hull boundary, indicating shape irregularity.

Classification and Decision-Making Combining these features, machine learning methods (such as SVM or decision trees) classify eggs to determine the presence of cracks.

### Extended Approaches For eggs with complex textures (e.g., speckle interference), techniques like Local Binary Patterns (LBP) or Gabor filters can enhance contrast in crack regions. In dynamic detection scenarios, algorithm speed can be optimized using GPU acceleration (via MATLAB's Parallel Computing Toolbox) for real-time performance.

This method enables efficient crack detection in eggs, enhancing automated sorting efficiency and reducing manual inspection errors.