Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/392 2018 2018 Bharati Vidyapeeth’s College of Engineering, New Delhi, India Hardik Agarwal Bharati Vidyapeeth’s College of Engineering, New Delhi, India Kanika Somani Bharati Vidyapeeth’s College of Engineering, New Delhi, India Shivangi Sharma Bharati Vidyapeeth’s College of Engineering, New Delhi, India Prerna Arora Bharati Vidyapeeth’s College of Engineering, New Delhi, India P. Singh Lamba Bharati Vidyapeeth’s College of Engineering, New Delhi, India Gopal Chaudhary In this paper, unique features of the segmented image samples are extracted by using two major feature extraction techniques: Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). After this, these features are fused to get more precise and productive outcomes. The average accuracy of the three distinct datasets that were generated using the LBP and HOG features are determined. To calculate the accuracy of the three distinct models, classification techniques like KNN and SVM, are adopted. 2020 2020 22 31 10.54216/FPA.010103 https://www.americaspg.com/articleinfo/3/show/392