Improving feature extraction using Part Separating algorithm : Case study forinsect identification of Order Lepidoptera

In Automated Insect Identification (AII) research field, several researches focused on the feature in feature extraction that effective for insect classification in different taxonomic level. General taxonomic features from each taxa such as color, texture and shape were extracted and combined into a single value from the whole insect body. This paper was to develop feature extraction in AII for families identification of Order Lepidoptera by using Part Separating algorithm (PS), which generates a single feature value by separating feature from the whole insect body into five values. The five features were extracted from head part, front-wing part, back-wing part, abdomen part and symmetry half,the extracted feature related with each other. This proposed algorithm developed feature extraction method for family's identification at Order Lepidoptera. In result, proposed algorithm has accuracy 97.27 % at family Sphingidae.