This work uses GP to identify specific features on an image using linear and tree genome representations. Grammatical Evolution (GE) is used to represent linear GP using a BNF (Backus Naur Form) grammar. Tree-genome however, is used to represents GP individuals in the form of binary trees. Panmictic model was used to implement the tree-based GP. A non- parametric analysis is performed on results of the computer vision problem to measure statistical significance between both representations at 95% significance level. Mann-Whitney test performed on the results show that linear-genome representation (using GE) outperformed tree-genome representation and is further supported by other key performance indicators.
Linear Representation: Grammatical Evolution in Java
Tree Representation: Evolutionary Computation in Java
Data Processing: Java + Shell Scripting