Genetic algorithms to automatic weld bead detection in double wall double image digital radiographs

This paper presents a pioneering approach for weld bead detection in radiographic images obtained by the Double Wall Double Image (DWDI) technique. Such task constitutes an essential step for several high level processes, such as fully automatic flaw identification on welded joints. Sets of sample pixels, corresponding to candidate solutions provided by a genetic algorithm (GA), are compared to pre-defined synthetic weld bead and pipe models in an image matching procedure. The fitness of each set (individual) is evaluated based on a linear combination of its genotype (evaluated by a heuristic function) and phenotype. The evolutionary process automatically selects the best individual in the population and, thus, provides information such as position, orientation and dimension of the detected object. The proposed approach successfully detects pipes and weld beads in radiographic images of different complexities, encouraging future works.