Fig. 2

Fig. 2

Segmentations by different methods for a zebrafish specimen in lateral position. Blue bounding box indicates the expected segmentations, and red bounding box indicates inaccurate segmentations. a Segmentation by the geodesic active contours (GAC) model. Due to the edge sensitivity, the GAC model fails to detect the tail of the specimen. b Segmentation by Chan–Vese (CV) model. The partial transparency of the specimen makes it difficult for a region-based method to discriminate the object from the background. c Segmentation by a local region-based level set (LRLS) model. Similar problem occurs that the tail of the specimen is incorrectly segmented. d Segmentation by an improved level set (ILS) method. e Segmentation by mean shift (MS) algorithm. Better results are obtained though; edge sensitivity becomes worse. f Segmentation by the proposed hybrid (HY) method. The accurate segmentation presents a natural and compact shape description for the zebrafish specimen (colour figure online)