摘要
在分析了不同图像分割方法的基础上提出了一种基于颜色特征和纹理特征的图像分割算法,以解决复杂背景下苹果采摘机器人分割目标与背景的问题。通过分析灰度图像的纹理特征,求取灰度共生矩阵提取特征,以支持向量机分割图像,并结合HSI颜色空间的色差特征达到目标和背景分离的效果。通过与单纯的颜色特征分析和纹理特征分析相比较,该方法在识别率上高于其他分割算法,同时对于颜色与背景相近的果实也能有很好的分割效果。
This paper, after analyzing different image segmentation methods, presents an image segmentation algorithm based on color and texture features in order to enable an apple picking robot to separate targets from complex backgrounds. Texture features of grayscale images are analyzed to obtain ground launched cruise missile for feature extraction and to segment images by support vector machine. Besides, in combination with chromatic aberration in HSI color space, targets are effectively separated from their backgrounds. By comparison with the methods of color analysis and texture analysis, this algorithm provides higher rate of recognition and ever better result in separating fruits with similar colors to backgrounds.
出处
《图学学报》
CSCD
北大核心
2016年第5期688-693,共6页
Journal of Graphics
基金
国家自然科学基金项目(61308120)
关键词
灰度共生矩阵
HSI空间
支持向量机
分割
gray level co-occurrence matrix
HSI space
support vector machine
segmentation