Spatial collaborative representation for image categorization

A novel proposed approach, collaborative representation-based classification, has been developed for face recognition and recently used in image classification task owing to its simplicity and effectiveness. The major drawback of this method is the neglect of the spatial structure among the image representations. Inspired by the success of this technique and motivated by the power of spatial information in improving the image representation, we suggest in this paper a novel collaborative approach named spatial collaborative representation based classification. After applying the feature encoding and the pooling method, we exploit the global manifold structure of the image by applying the spatial pyramid representation. After that, two successive steps are required in order to obtain the label category for each image. In the first step we apply the standard collaborative method for each histogram generated at each pyramid level. The second stage aims to combine efficiently the image reconstruction results in order to predict the category label.