On the Application of Orthogonal Series Density Estimation for Image Classification Based on Feature Description

This paper presents an image classification algorithm called density-based classifier. The proposed method puts together the image representation based on keypoints and the estimation of the probability density of descriptors with the application of orthonormal series. For each class of images a separate classifier is constructed. The presented procedure ensures that different descriptors affect the final decision in a different degree. The trained classifier determines whether the query image is assigned to the class or not. The obtained experimental results show that proposed method provides good results. The algorithm can be applied to many tasks in the field of image processing.

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