Curvature Scale Space Application to Distorted Object Recognition and Classification
Natan Jacobson, Truong Q. Nguyen, Frank J. Crosby · 2018 52nd Asilomar Conference on Signals, Systems, and Computers · 2007
Contour classification methods which operate directly on an image are greatly affected by small magnitude transformations to the image. In this paper, a contour classification method is developed which takes advantage of curvature scale space (CS2) and a linear support vector machine (SVM) classifier. The CS2representation boasts invariance to transformations including: scaling, rotation, translation and noise. In addition, the linear SVM is a robust tool for classification problems involving multiple labels. The combination of these tools produces a classifier well suited for object recognition in photographs where distortion is present.