An algorithm for segmenting gaseous objects on images

A new methodology for segmenting gaseous object images is introduced. Unlike in case of a rigid object, the edge intensity of a gaseous object varies along the object boundary (edge intensities of some pixels on a gaseous object boundary are weaker than those of small rigid objects or noise itself). Therefore, the conventional edge detectors may not adequately detect boundary-like edge pixels of gaseous objects. We develop a novel object segmenting method using fuzzy algorithm trained by the genetic algorithm. The proposed method consists of a fuzzy-based boundary detector applicable to gaseous as well as rigid objects, and concave region filling to recover object regions. This algorithm is well applicable to medical image such as breast cancer or tumor segmentation.