Analysis of Image Classification using SVM
Sai Surya Teja Gontumukkala, Yogeshwara Sai Varun Godavarthi, Bhanu Rama Ravi Teja Gonugunta, R Subramani, Keerthna Murali
Abstract
Image classification is one of the classical image processing problems. There are various approaches such as Support Vector Machine, Artificial Neural Networks, Convolutional Neural Networks, K-Nearest Neighbors and Decision Tree for solving this problem. In this paper Support Vector Machine (SVM) is used to classify Images and we are trying to understand SVM and then understand how to draw a decision boundary and try to make it optimal and use it for classification. Two Datasets “Dogs Vs Cats” and “Color Classification” are used in this paper.
Topics & Concepts
Support vector machinePattern recognition (psychology)Computer scienceContextual image classificationArtificial intelligenceImage (mathematics)Computer visionFace and Expression RecognitionText and Document Classification TechnologiesImage Retrieval and Classification Techniques