【摘要】 提出一种基于颜色及梯度统计特征的结核杆菌目标识别算法。首先基于HSV颜色空间进行图像预分割,然后在CIE L*a*b*颜色空间进行自适应分割以提取目标精细几何形状。为了适应背景的复杂变化,基于色调一致性假设对疑似目标进行色调一致性检验并剔除大部分伪目标。为了将重叠粘连目标从伪目标中分离出来,提出两个梯度统计特征,然后结合目标的面积、周长、长宽比、圆形度、粗糙度等形态特征,组成7维特征向量送入贝叶斯分类器进行分类。实验结果表明,本文算法能适应标本、染色及图像背景等复杂变化,目标识别率可达91%。更多还原

【Abstract】 A color and gradient feature based image segmentation and recognition algorithm is proposed for Mycobacterium Tuberculosis(TB) objects in microscopic images.First,the input color image was pre-segmented based on the HSV color space using the threshold method according to the prior information.Then,the original image was transformed to the CIE L*a*b* color space,and the L component image was segmented using an adaptive threshold method to get finer segmentation result.In order to accommodate the complex variety of image background,all the suspected objects were verified according to the "hue consistence" assumption and the false objects were rejected.To identify the TB bacilli,the algorithm used five shape feature descriptors,including the area,the perimeter,the ratio of width to height,the compactness and the roughness,and two gradient feature descriptors,the gradient magnitude weighted average(GMWA) and the gradient magnitude variance average(GMVA) respectively,and makes the judgment through Bayes classifier.Experimental results show that the proposed algorithm can accommodate the complex variety of specimens and the image background,and a high recognition rate(91%) can been obtained.更多还原