The Application of Image Recognition System in Identification of Common Butterflies in Taiwan

• Main Authors: Hsin-Fu Wang, 王信夫
• Other Authors: Cheng-Jen Shih
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/02930202841202217984

碩士 === 國立臺灣大學 === 昆蟲學研究所 === 100 === The availability of 400 species of butterflies in Taiwan is an example of high species richness that is opening opportunities for great science education, but it also could be a challenge of being a material of science education. The difficulties during species identification may create misunderstanding for learning or seeking further information. People usually identify insects comparing the similarity between insects, pictures and descriptions on illustrations. However, these inconveniences, requirements of high knowledge and experiences could left many people behind the knowledge or lose their interest on insects. To breakthrough these barriers, developing a new innovative system that could automatically identify insect species is the one solution. To make that possible, first we define the common butterfly species in Taiwan as the butterflies that have stable population, easy to obtain, or famous species. By photograph, well-identified specimens in NMNS, that butterfly was taken as a test insect and a database images of common butterflies in Taiwan was established. The application of the image recognition techniques to analyze the database images and the pictures captured in natural environment, finding the similarities and differences for in the reorganization of butterfly species were accomplished. The identification characteristics included are colors, patterns and the information link with images captured as time and location. The HSV color model was applied and compared with its histogram, and SURF was used to identify the specific pattern of butterfly. To correct the identification method into most effective way, series of tests were designed by recognizing the texting images which were modeling from ranges of situations in natural images, and the results are expected to be used to adjust the parameters. This work aimed to develop a system that can be broadly applied in cell phones or other photographable communication equipment to enhance the knowledge that ultimately improve the usage value of insect as science education material.