一种基于差分算子和区域增长的细胞自动识别方法

为了实现血细胞图像的自动识别，提出了一种基于差分算子和区域增长的方法。该方法在边缘分割的基础上．利用差分算子分别求出细胞的灰度上升区域和下降区域，然后采用改进的区域增长法求出各自的区域数，最后通过BP神经网络进行训练和识别。实验结果表明，该方案运行速度快，识别率高，具有较好的实用价值。

A New Approach for Cell Automatic Recognition Based on Difference Operator and Region-growing

This paper proposes a new approach based on difference operator and region-growing to automatically recognize cell image. Basing on edge segmentation, two kinds of areas are found by using difference operators, one kind with increasing gray value and the other with decreasing gray value. Then the respective numbers of the two kinds are gained by using improved region-growing method. Finally these numbers are utilized to train BP neural networks, which can be used to recognize cell image. The experimental results show good performance on running speed, accuracy and practical application.