Shellfish Recognition Based on Gabor Transformation and Principal Component Analysis

In this paper, a method of shellfish recognition based on Gabor transform and two-dimensional image principal component analysis (2DPCA) is studied. Gabor transform is used to extract the image features and determine the dimension of the image features; The 2DPCA method is used to reduce the dimension of the transformed features. Compared with BP neural network and support vector machine (SVM) experiments, the results shows that the extreme learning machine classifier is very fast, which has good generalization and high accuracy.