Linear Derivative-Based Approach for Data Classification

In computer vision, object classification is the most essential stage for recognizing the class of the image using its features. Many models have been presented in the last few years for the classification of still images. A simple linear classification technique with moderate accuracy and low run-time complexity for still images is proposed in this paper. The proposed scheme is compared with the other state-of-the-art techniques and experimental results show the effectiveness of the proposed scheme in terms of time complexity. Thus, the proposed work can be proved beneficial for real-time applications where low computational time is required.