Field monitoring support system for the occurrence of Leptocorisa chinensis Dallas (Hemiptera: Alydidae) using synthetic attractants, Field Servers, and image analysis

To realize effective insect counting in pheromone traps set in remote sites, a remote monitoring and image processing system based on a sensor network system of “Field Servers” has been developed, and two practical methods based on image analysis using this system has been proposed. This system has been employed to monitor the occurrence of the rice bug, Leptocorisa chinensis, in rice paddy fields as a means of reducing the burden of manual insect counting work.A Field Server with a high-resolution digital camera was installed near the pheromone trap for close monitoring. The image data and other monitoring data such as temperature were sent via wireless LAN and the Internet every 5 minutes. A remote management system for the Field Server, located about 7.5 km from the experimental field, managed data collection and analyzed the data to provide useful information on insect count. An image analysis algorithm based on a background differencing technique has been developed to support counting L. chinensis by implementing an image-processing module in the remote management system. The image-processing module provides three analysis functions: cropping, subtracting, and binarizing the target image.One method is to filter extraneous image data containing no observed target insects (end-members) on the pheromone trap. In this method, the difference between collected image data and the reference image data was calculated, and the total number of pixels whose value was greater than a threshold value for the difference result (number of white pixels) was used for filtering. This method managed to maintain Sensitivity at 100% during the experiment. Accuracy was observed to be 89.1% on average. Using this method, the time spent looking at extraneous image data without L. chinensis can be reduced by 85%.The other method for reducing labor in counting involves estimating the number of end-members automatically using a partial image area that is cropped to focus on a low-noise area, permitting easy analysis. With this method, the image data was analyzed using the first method, and the entire number of end-members was estimated using the number of white pixels and a pixel value equivalent to one end-member. The results of this method correspond reasonably closely to the results obtained by manual counting. The correlation coefficient for the daily occurrence rate was 0.974 and that for the hourly rate was 0.916.

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► We have developed a remote pheromone trap monitoring system with image data based on sensor network and image processing.
► This system was applied to measure the occurrence of the rice bug, Leptocorisa chinensis, in a rice paddy field.
► This system provides a method of filtering out extraneous image data using our proposed image analysis algorithm.
► A method was also developed to automatically estimate the number of target insects from captured image data.
► The results of these methods showed the system effectively reduced the labor required to count target insects.