A multiple method fusion image acquisition and processing system based on machine vision technology which applies to detecting tomatoes external quality is designed to solve the problem of low efficiency and strong subjectivity of artificial detection. Firstly

the color histogram is used to obtain the color features of tomatoes. Then

the characteristics of tomatoes' shape is described after calculating the irregular degree by using the boundary tracking algorithm which could get the radius of tomato sequence points and the Fourier transform and inverse transform. In the meantime

a deformation of Green's formula is introduced into obtaining tomato centroid coordinates and the maximum transverse diameter to identify the size. Finally

according to previous image information such as size

color and shape feature

tomatoes are graded effectively by using pattern classifier based on linear discriminant function and decision tree. The classification accuracy is improved to 92% and the stability of classification results of the system are proved by experiments.