Shape Characterization on Turtle Detection

Abstract

All sea turtles are considered as endangered and threatened that is affected by some natural and other caused by human activities. One of the problems faced on fishing operation is caught on gill net. Turtle Excluder Device (TED) is developed to prevent turtle approaches the net by dispels the sound signal. The objectives of this research project is to develop a system for identify the presence of turtle by using shape characterization. Turtle identification deployed by using underwater video camera with implementation of MATLAB software. The Green turtle (Chelonia Mydas) for various ages are used. The parameters are the head, tail, flippers and carapace of orientation. The characterization of parameters identified based on the analysis on image processing. The shape parameters of flippers are shown as the most identified. The orientation front and side easily to recognize the turtle present. In addition, for detection of turtle should over than 5000 number of pixels is identified as a turtle. This information will used to identify the turtle and prevent caught in the fishing net using improvement of TED with sound signal and image detection. Therefore, the endangered turtle can be protected and fisherman also can improve their efficiency and help to safeguard marine ecosystems.