MACHINE VISION GRADING OF PISTACHIO NUTS USING GRAY-LEVEL HISTOGRAM

A machine vision system was used to classify ''in the shell'' pistachi o nuts based on USDA grades. The gray-level histogram data obtained fr om the gray scale image of the nuts were analyzed to select a set of s uitable recognition features. Based on the analyses, the mean of the g ray-level histogram over 50 to 60 gray-level range and the area of eac h nut (the integral of its gray-level histogram) were selected as the recognition features. The selected features were used as input to thre e classification schemes: a Gaussian, a decision tree, and a multi-lay er neural network (MLNN). The three classifiers had similar recognitio n rates. However, the MLNN classifier resulted in slightly higher perf ormance with more uniform classification accuracy than the other two c lassifiers.