Fish fry counter based on digital image processing method

Abstract

Large quantities of ornamental fish fry can be time-consuming and error-prone to count manually. The tedious counting of ornamental fish fry can also be stressful and result in the death of the fish fry, which can result in lost sales for ornamental fish businesses. In order to solve these issues for the ornamental fish businesses, the goal of this research is to develop a system for automatically counting the number of fish fry using the thresholding and morphology methods based on digital image processing. The fish fry counter has been tested with four distinct types of fish fry, is capable of counting up to 130 fish fry in 1-3 seconds for a single operation. The final result generated by this tool are an image with a description of the total number of fish fry encountered, the date and time of data collection, and the number of fish fry detected. This information are stored in a database with .xlsx extension. The experiments result appears that this tool can count the number of fish fry corresponding to different colored fish species. However, when calculating the total amount of fish fry that can fit into the container to its full capacity, the tool has an accuracy of 95.86% and an average error of 4.14% that is caused by the side of the container which contains fish fry that are not visible to the detection camera (blind spot).