AI-Based Bread Quality Assessment using Image Processing Techniques

This dataset supports the study titled “AI-Based Bread Quality Assessment Using Image Processing Techniques and the Developed BQe-CNN”. It contains annotated images of bread slices that vary in quality based on attributes such as color, porosity, and crumb texture. Each image was processed using advanced image processing techniques including grayscale conversion, adaptive thresholding, morphological operations, and edge detection. These steps support feature extraction for training the Bread Quality Enhanced Convolutional Neural Network (BQe-CNN), a deep learning model designed specifically for visual quality inspection in bread manufacturing.