Real time fruits quality detection with the help of artificial intelligence

Abstract

One of the major quality of grading fruits is its appearance. Appearance is effects the marketing and choice of consumer. Colour, texture, size, shape are used to find quality of fruit. But the sellers controlling the external quality of fruits to get high profit. In earlier observations, implemented products, computer vision systems for external controlling quality so grading and classification of fruits is based on observations. The proposed system depend on image processing to classify and grade quality of fruits by using mean of image, colour and HOG (Histogram of gradient) feature extractions are used to classify the fruit quality. All machine learning algorithms are used to find the better accuracy of data how it is predicting. In proposed method first data set is collected, then pre-processing is applied for better results. Machine learning algorithms (K-nearest neighbour (KNN), Support Vector Machine (SVM), and PCA is used for dimension reduction and to get good accuracy to implement the system. For big data pre-processing and to get better results Deep learning (CNN) is used to test the fruit in real time world with result and audio sounds. Audio is used to detect object by hearing also.