Automation is used to boost production, quality, and profitability for the nation. Fruit sorting and grading is an essential procedure for fruit producers since it impacts the quality of the fruit as well as the market for exports. Human grading and sorting are feasible; however, it is very time-consuming, labor-intensive, and a tedious work. As a result, an advanced fruit sorting and grading the system are necessary. Using computer vision, researchers have developed several fruits sorting algorithms in recent years. The most frequent criteria used to detect illnesses, ripeness, and a class of fruits is color, textural, and morphological characteristics. Clustering and color-based segmentation, artificial neural networks, and other classifiers based are some of the techniques used. The study of various fruit detection systems is the major focus of research work nowadays. These characteristics are then utilized to train a soft computing method network. This study examines the use of image processing in agriculture to give insight into the usage of vision-based systems by highlighting its benefits and drawbacks