Automatic classification of web images as UML diagrams
Valentín Molina Moreno, Gonzalo Génova, Manuela Alejandres, Anabel Fraga · 2016
Our purpose in this research is to develop a methodology to automatically and efficiently classify web images as UML static diagrams, and to produce a computer tool that implements this function. The tool receives as input a bitmap file (in different formats) and tells whether the image corresponds to a diagram. The tool does not require that the images are explicitly or implicitly tagged as UML diagrams. The tool extracts graphical characteristics from each image (such as grayscale histogram, color histogram and elementary geometric forms) and uses a combination of rules to classify it. The rules are obtained with machine learning techniques (rule induction) from a sample of 19000 web images manually classified by experts. In this work we do not consider the textual contents of the images.