Publication

Abstract : Image recognition and classification plays an important role in many applications, like driverless cars and online shopping. We present the classification of Fashion-MNIST (F-MNIST) dataset using HOG (Histogram of Oriented Gradient) feature descriptor and multiclass SVM (Support Vector Machine). In this paper we explore the impact of one of the successful feature descriptor on Fashion products classification tasks. We have used one of the most simple and effective single feature descriptor HOG. The multiclass SVM which is one of the best machine learning classifier algorithms is used in this method to train the images. Selecting appropriate technique for feature extraction and choosing a best classifier algorithm remains a big challenging task for attaining good classification accuracy. However, the experimental results show that impressive results on this new benchmarking dataset F-MNIST.