一种多目标快速识别的自适应灰度量化方法研究

针对实时序列图像多目标识别问题提出了一种快速图像处理方法。该方法依据一定的先验知识和准则，对复杂背景图像进行窗口化，对每一个窗口独立进行自适应快速中值滤波，及基于局部图像灰度信息的自适应重新量化和最大熵分割处理，实现了对全景视场内预定目标的快速准确提取和识别。为动态环境中多目标条件下移动机器人的视觉定位、导航和目标跟踪所需图像处理技术提供了一种新的方法。

This paper proposes an image processing method.Based on some advanced knowledge and rules, the multi-window architecture is used. A self-adaptive re-quantization and max entropy threshold are used to segment the images in these windows. Then, the defined targets in sequence images are fast extracted and recognized. This method can be used for mobile robot visual positioning, navigation in global environments.