摘要
基于内容的图像处理与分析技术,其基本前提是确定图像中包含的内容,即具有语义的内容对象。图像分割技术是实现图像内容对象检测的基本方法。对图像分割中的必要性问题进行了相关研究,针对大部分图像分割算法因所分割的图像不具有语义信息而导致图像分割出现无意义情况的现状,提出了一种图像分割复杂性的定义。基于该定义,给出了其实现方法。通过系统的实验结果表明,所提出的新的图像分割复杂性指标可以很好地适应图像目标区域大小,是衡量图像分割必要性的一种合理有效的方法,且能够成为一种重要的图像分割判断指标。
The basic foundation of processing and analysis technology of image is confirming the content of image,namely with semantic content object.The existing image segmentation algorithms make segmentation areas only accor-ding to the color,and texture.Therefore it does not have any semantic information.Aiming at this issue,the necessity of image segmentation problem was analyzed,and the definition of a new image segmentation necessity evaluation index was proposed,and also,the judgment procedure and realization method were provided based on this index.The experimental results show that compared with the existing image segmentation method,the proposed image segmentation necessity index has very good adaptability to the target area size,and it can be an important measure and effective method to the necessity of the image segmentation.
出处
《计算机科学》
CSCD
北大核心
2013年第4期310-313,共4页
Computer Science
基金
国家自然科学基金项目(61202285)
河南省科技厅科学技术重点项目(12A510001)资助
关键词
图像
复杂性
测度
分割
Image
Division
Complexity
Measure
