杏鲍菇形态特征获取的图像分割算法

食用菌工厂化生产中，菇房环境对食用菌生长的影响很大，由工人根据食用菌的形态特征来判断菇房环境是否适宜，会由于个体主观差异或人为因素不能及时判断，造成菇房环境调节滞后，影响了食用菌的产量和质量。以杏鲍菇为研究对象，提出了获取杏鲍菇形态特征的蚁群算法改进的模糊C均值（FCM）聚类分割算法，该算法能够针对杏鲍菇生产中获取的图像，进行有效地分割，从而满足自动获取杏鲍菇形态特征的需要。

Segmentation Algorithm for the Image of Pleurotus Eryngii Morphological Features

In the industrial production of edible fungi, the environment has a great influence on the growth of edible fungi. Because the judgment results of the environment suitability by the workers in accordance with the morphological characteristics often are of subjective individual differences and due to human factors, the judgment can not be made in time, the regulation of environmental usually is lagged so as to influence the production and quality of the mushroom. The fuzzy C-means （FCM） clustering segmentation algorithm was proposed to obtain morphological features of Pleurotus eryngii, based on improved ant colony algorithm. The algorithm can effectively segment the images derived from the production of Pleurotus to meet the needs of automatic acquisition of Pleurotus morphological features.