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A research based on recognition algorithm of characteristics of body surface of infected fish

机译:基于识别算法的被感染鱼体表特征研究

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The contents of this research is how identify an infected fish through analysis of it's image to get from the monitoring aquaculture process by computer. By studying recognition algorithms about surface images of infected fish, we identifie automatically fish diseases by computer and no need of manual intervention it. The early warning from computer makes it possible to take measures to prevent and save the loss and damages in fishing industry intensive and high-density. In accordance with fish's own body color characteristics of a large contrast, we use Dual-threshold Difference-image Method to extract it's contour, then can make fish's image a structural segmentation according to the proportion of it's head,tail and body, and further extract their color and texture feature vector in order to compare the surface feature vectors with that normal fish have ownned, we can find some infected fishes or no, and even the type of fish diseases.
机译:这项研究的内容是如何通过对其图像的分析来识别受感染的鱼类,并通过计算机从水产养殖监测过程中获得鱼类。通过研究有关被感染鱼类表面图像的识别算法,我们可以通过计算机自动识别鱼类疾病,而无需人工干预。来自计算机的预警可以采取措施,防止和节省集约化和高密度捕捞业中的损失和损害。针对鱼自身的大对比度色彩特征,采用双阈值差分图像方法提取鱼的轮廓,然后根据鱼的头,尾,身比例将鱼的图像进行结构分割,进一步提取为了比较表面特征向量和普通鱼类拥有的颜色和纹理特征向量,我们可以发现是否有被感染的鱼类,甚至没有鱼类,甚至是鱼类疾病的类型。

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