Automatic Segmentation Method for Live Fish Eggs Microscopic Image Analysis

Automatic visual inspection (AVI) is a popular tool for object detection and analysis in many fields. In fisheries, AVI systems designed for fish egg development analysis are used for fish egg assessments in commercial and experimental fish production systems and in ecological monitoring. The first step in AVI systems is to subdivide an image into meaningful regions. The accuracy of this segmentation directly influences the success of subsequent image analysis operations such as feature selection and classification. At present, a lot of image segmentation techniques are available, but there is no universal segmentation technique suitable for all kinds of images. This paper presents a cascading automatic segmentation method for microscopic digitised images of live common carp (Cyprinuscarpio) eggs in Petri dishes filled with water. The proposed method involves five main steps:1) image pre-processing, 2) image initial segmentation by Otsu's method, 3) segmentation post-processing based on morphological operations, 4) image edge detection and morphological operations to remove incomplete eggs, and finally 5) a Watershed method was used to resolve the problem of separating adjoining fish eggs. Testing the method in Matlab software verified that fish eggs were recognized, segmented and counted with 100% accuracy compared to manual observation in all 96 test cases.