A method of determining cut position of automatic stem removal system for salted wakame

In the wakame manufacturing procedure, the manual operation process of stem removal is known to hinder the production process. In order to solve this problem, the manufacture aspires to develop an automatic wakame stem removal system. The purpose of this paper is to propose a cut position detection method for the system by picking up the characteristic changes that appear at the cross section of the wakame. In this method, with the utilization of exposure control, two images are captured from the same cross section that is made by a developed device. These images are used in the segmentation of the cross section. The positions where the stem should be cut can then be determined through the examination of the thickness of the cross section. To test the performance of the proposed method, 100 cross sections were generated from the roots of 10 samples of the salt-preserved wakame with an interval of 20 mm. In the experiments, the proposed method gave good results to find the cut positions except some misdetection. The experimental results showed that this method is effective and usable to the automatic stem removal system

Automatic image enhancement by artificial bee colony algorithm

editor: Zeng ZhuWith regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on Artificial Bee Colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local and global information of the image. In order to solve the optimization problem by ABC algorithm, an objective criterion in terms of the entropy and edge information is introduced to measure the image quality to make the enhancement as an automatic process. Several images are utilized in experiments to make a comparison with other enhancement methods, which are genetic algorithm-based and particle swarm optimization algorithm-based image enhancement methods