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This study is proposed on detection of Echizen Jellyfish from the images which were anonymously uploaded to the internet. The outbreak of Echizen Jellyfish will seriously damage the fishery of Japan. In this work, a machine learning algorithm such as SVM with the HOG feature was employed. All of the test images were gathered from internet. There is no need to install underwater camera, and this method can reduce cost for detection. Also real observation requires many human resource and time. On the other hand, proposed method requires no extra people and can detect the jerry fish via internet images timely. In this method, precision is lower than real observation, but such an error can be canceled because what we need is the relatively appearance frequency for a limited time span consequently. The evaluation of this system is performed by using the F-measure. F-measure is a comprehensive evaluation of the precision and recall. The final goal of this study is detect Echizen Jellyfish from internet automatically without human interaction and extra cost. As a previous step in this work the detail of detection algorithm is discussed.

The Study of Detection Method of Echizen Jellyfish Using Images from the Internet