Fruit Quality Detection Using CNN

In todays world where our daily diet mainly consist of junk food, consumption of good quality fruits have become a necessity. Rather than consuming fruits , our main focus must be towards the quality of the fruits. So here comes the importance of a sytem ,which can sort fruits based on its quality , as sorting fruits by human labour is time consuming and also chance of causing error are more comparing to a machine. Therefore we have devised a model to classify fruits based on their appearances to good/bad. The model mainly make use of Machine Vision Techniques[1] to identify the images of fruits. Processing the outer appearance is the primary step. Then the captured image is preprocessed where the important features like the colour or any black spots or any formation of mould or funguses are detected. The captured images are normalized and the data is also augmented in this step. The image preprocessing[2] helps in classification and comparison of image during both training and testing. The model that we selected is Convolutional Neural Network(CNN)[3] Model. This model comes under Deep Learning[4]. KEYWORDS: Machine Vision [1], Deep Learning [4] , Image Processing [2], Machine Learning [7], Normalization [6], Convolutional Neural Network (CNN) [11].