Comparison of Pattern Classification Methods in Discrimination of Inferior Shijimi Clams by Acoustic Signal

In this paper, we compare the pattern classification methods to discriminate the inferior shijimi clams with aim at development of the selecting device for shijimi clams. In our framework, the feature vectors are extracted based on frequency analysis of the acoustic signal that occurs in hitting shijimi clams themselves, and then shijimi clams are classified by the pattern classification methods such as decision tree learning, multilayer perceptron, k-nearest-neighbors classifier and linear discriminant analysis. Through the experiment, we confirm the effectiveness of our framework.