Feature Evaluation for Building Facade Images — An Empirical Study

Image classification are critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, peucker features, texture features, and SIFT features. We present an approach for regionwise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification with eTRIMS database, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.