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Image recognition of juvenile colonies of pathogenic microorganisms in the culture based microbiological method implemented in bioMEMS device for express species identification

机译:在基于BioMEMS的表达物种识别装置中基于培养的微生物学方法中病原微生物少年菌落的图像识别

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In this paper an image recognition method for microbiological analysis of species is described. This method is developed for use in bioMEMS hybrid laboratory-on-a-chip for total microbiological analysis and is aimed at recognition of colonies of microorganisms for express species identification and sorting. The described approach is based on the Histograms of Oriented Gradients (HOG) method, developed earlier. A principle of this technique is the computation of intensity gradients directions in local areas of image and determination of objects affinity using special classifier. The method is widely used for people identification, where it proved to be very efficient. In microbiology it appeared to be not as successful, because images of single microorganisms and their colonies are too similar. Here an advanced version of HOG is presented, which enabled a number of microbiological species to be identified. The method comprises the following stages: 1) Initial image acquisition; 2) Search and retrieval of the colony; 3) Simplification of the image, transition to local gradients of the grey; 4) Processing with threshold noise filter; 5) Fourier-transform of local gradients of the grey; 6) Formation of classifier by teaching the expert system by comparison with reference images. The described method is applied for recognizing colonies at earlier stages of growth (juvenile colonies) incorporating about 1000 cells. A sample of investigated microorganisms comprised 18 species from 8 different genera.
机译:本文介绍了一种用于物种微生物分析的图像识别方法。该方法被开发用于生物MEMS混合芯片实验室中的总微生物分析,旨在识别微生物菌落以进行快速物种鉴定和分选。所描述的方法基于先前开发的“定向直方图”(HOG)方法。该技术的原理是计算图像局部区域中的强度梯度方向,并使用特殊的分类器确定对象的亲和力。该方法被广泛用于人员识别,事实证明该方法非常有效。在微生物学上似乎并不那么成功,因为单个微生物及其菌落的图像太相似了。在此介绍了HOG的高级版本,该版本可以识别多种微生物。该方法包括以下步骤:1)初始图像获取; 2)搜集殖民地; 3)简化图像,过渡到灰色的局部渐变; 4)用阈值噪声滤波器处理; 5)对灰色局部梯度进行傅立叶变换; 6)通过与参考图像进行比较来教授专家系统,从而形成分类器。所描述的方法用于识别结合了约1000个细胞的生长早期阶段的菌落(幼稚菌落)。被调查的微生物样本包括来自8个不同属的18种。

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