Data Generation and Fruit Grading Using Different Classifiers.

Grading of fruits is the post harvesting step involving the labeling of fruits into their respective categories using external (color, size, shape etc) and internal features(aroma, taste, pH etc). This could be done manually which is tiresome, inconsistent and time consuming task and therefore computer vision based fruit grading comes into play which makes the whole grading process consistent, labor saving and fast as well. In past years, researchers had introduced many non destructive image processing technique to grade the food products, ensuring quality of food products. This paper presents algorithm of classifying guava fruit into categories using Local Tetra patterns. Features extracted are classified using SVM, K-NN, Trees, ANNs. Results generated by different classifiers are analyzed using accuracy and error rate. Linear layer neural network gave the highest results amongst all the classifiers. [ABSTRACT FROM AUTHOR]