In this paper, we propose a method to detect a road sign from a road scene image in the daytime. In order to utilize color feature of sign efficiently, color distribution of sign is examined, and then color similarity map is constructed. Additionally, color similarity shown on the map is incorporated into image energy of an active net model. A road sign is extracted as if it is wrapped up in an active net. Some experimental results obtained by applying an active net to images are presented.

Processes in image recognition include target detection and shape extraction. Active Net has been proposed as one of the methods for such processing. It treats the target detection in an image as an energy optimization problem. In this paper, a problem of the conventional Active Net is presented and the new Active Net is proposed. The new net is improved the ability for detecting a target. Finally, the validity of the proposed net is confirmed by experimental results.

In the culture of marine chlorellas, it is necessary to count the number in order to understand the condition of increase. For that propose, counting by the naked eye using the microscope has been used. However, this method requires a lot of time and work. We have developed the automatic chlorella counter using image processing and neural network. Its effectiveness is confirmed through the experiment.