中文摘要：

为降低算法的计算复杂度、加快搜索速度，将人工鱼群算法（AFSA）用于最大熵多阈值的快速寻优，提出了一种基于人工鱼群算法的最大熵多阈值的成熟草莓图像闽值分割算法（AFSAMEMT）。首先提取RGB彩色图像的R分量灰度图像及灰度图像信息．然后设计多阈值整数编码并将最大熵转化为编码的目标函数，最后利用AFSA寻优求得最大熵及其对应的阈值，进行图像分割。结果表明，AFSAMEMT相对OTSU等图像分割算法在复杂环境下不仅能达到更好的分割效果，而且有更好的分割效率。

英文摘要：

Aiming to reduce the computational complexities and accelerate the search speed, the artificial fish algorithm（AF- SA） was introduced to more rapid optimization of maximum entropy multiple threshold, a novel maximum entropy multiple threshold strawberry image segmentation method （AFSAMEMT） based on AFSA was proposed. Firstly, the R component gray images of RGB color images and their gray image information were extracted, and then the multiple threshold integer coding was designed and the maximum entropy was converted to the coding corresponding objective function, finally, the maximum entropy and their corresponding thresholds were obtained by AFSA and the images were segmented. The experimental results showed that AFSAMEMT algorithm in a variety of complex environments could not only achieve better segmentation effect than OTSU algorithm, etc, but also had better segmentation efficiency.