Abstract
Since Drosophila’s genes are 60% similar to human beings’, behaviors of Drosophila and human beings’ are alike such as sleep and courtship. Furthermore, the short life of Drosophila and the matured transgenic techniques make Drosophilae widely used in biological experiments, behavior research and neuroscience. However, most of experiments depend on labor to analyze the results. It is time-wasting and inefficient. In addition, data errors can be a big issue between experiments by different researchers. In the current study, image processing methods have been developed for monitoring the sleeping behavior of a Drosophila group and the behavior affected by different odors in order to increase the analysis efficiency and the correctness. In both algorithms, the frame difference method is used to capture the moving object/Drosophilae in the recorded video. Binarization and morphology methods are used to eliminate the noises. In addition, the overlapped Drosophila can be identified based on the morphology method. In the current sleeping calculator, the sleep period, the sleep bout number, the sleep bout length, the activity period, the activity bout number, the activity bout length, the rest period, the rest bout number, the rest bout length and the speed can be obtained. Besides, three states of Drosophila are redefined for better meaning. In addition, the image processing method is used to simulate the Drosophila Activity Monitoring System (DAMS), which is widely used for sleeping behavior of Drosophila in recent study. Image processing helps to increase the higher accuracy than DAMS does. The objective of odor algorithm is to develop a monitoring system which includes the air/odor flow equipment to study the behavior of Drosophila affected by different odors. With the help of these algorithms, higher experimented efficiency, accuracy and correctness can be provided.