Food Spoilage Detection Using Convolutional Neural Networks and K Means Clustering
This paper presents the novel idea for detecting food spoilage using image classification with machine learning algorithms and artificial intelligence technology. Food spoilage is detected by using artificial intelligence, deep convolutional neural networks, and computer vision and machine learning algorithms like k clusters algorithm for color classifications in images and its HSV values for spoilage detection. This project is done using the jupyter notebook platform through anaconda prompt. In this project, photos of food or fruits will be taken which have to be tested and then it will be processed through computer which will then perform image classification and machine learning algorithms for getting the colors in the image and spoilage is detected by HSV (Hue Saturation Value) values and percentages of each color which we have got by using the k cluster algorithms in jupyter notebook.
2019 3rd International Conference on Recent Developments in Control, Automation Power Engineering (RDCAPE)