Survey of Image Classification Based on Sparse Representation
Zhou Ji · Journal of Yancheng Institute of Technology · 2015
Good feature extraction method can reduce the workload of subsequent image classification and recognition. Different feature extraction methods are proposed for the specific classification problem,and achieved good results in image classification and recognition tasks. However,there are some obvious shortcomings of the existing feature extraction based on the traditional method. With the increasing of the size of the visual task,direct use of these traditional methods for feature classification is not ideal. The feature expression method is proposed,which is based on the most basic features of the image,and the sparse encoding or other expressions are proposed to form a final image. Based on sparse representation and its analysis,this paper focused on the feature classification algorithm and finally discussed the existing problems and future research directions.