A Novel Image Classification Algorithm Based on Extreme Learning Machine

In order to improve the accuracy and reduce the training and testing time in image classification algorithm, a novel image classification scheme based on extreme learning machine (ELM) and linear spatial pyramid matching using sparse coding (ScSPM) for image classification is proposed. A new structure based on two layer extreme learning machine instead of the original linear SVM classifier is constructed. Firstly, the ScSPM algorithm is performed to extract features of the multi-scale image blocks, and then each layer feature vector is connected to an ELM. Finally, the mapping features are connected together, and as the input of one ELM based on radial basis kernel function. With experimental evaluations on the well-known dataset benchmarks, the results demonstrate that the proposed algorithm has better performance not only in reducing the training time, but also in improving the accuracy of classification.