AI-Based Bread Quality Assessment using Image Processing Techniques

This dataset supports the study titled <i>“AI-Based Bread Quality Assessment Using Image Processing Techniques and the Developed BQe-CNN”</i>. It contains annotated images of bread slices that vary in quality based on attributes such as <b>color</b>, <b>porosity</b>, and <b>crumb texture</b>. 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 <b>Bread Quality Enhanced Convolutional Neural Network (BQe-CNN)</b>, a deep learning model designed specifically for visual quality inspection in bread manufacturing.