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A pattern matching scheme for accurate medicine localization in automatic pharmacy inventory

机译:自动药房库存中精确定位药物的模式匹配方案

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A vision based automatic pharmacy inventory is an unstructured environment in the sense that a random face of medicine box confronts the camera according to how it is put on shelf. This poses a challenge to traditional image content based object detection algorithms. In this paper we propose a shape-based medicine box localization framework. Instead of using feature point or texture based method which depends on image content, the proposed method adopts a pattern matching scheme, which takes advantage of the object's shape to build a synthetic pattern, for object localization. The superiority of our method lies in three-folds: 1) the proposed method is robust to frontal image content variation and does not depend on single image to make identification and localization; 2) the pattern matching scheme is robust to object perspective transform; 3) the method is insensitive to noises introduced by clutter environment, such as unbalanced illumination and reflection. To evaluate the proposed method, we test it in the real application environment. Large scale experiment shows the accuracy and robustness of our method.
机译:基于视觉的自动药房库存是一个非结构化的环境,从某种意义上来说,药箱的随机面孔根据其放置在货架上的方式与照相机相对。这对传统的基于图像内容的目标检测算法构成了挑战。在本文中,我们提出了一种基于形状的药箱定位框架。提出的方法不是使用依赖于图像内容的基于特征点或纹理的方法,而是采用一种模式匹配方案,该方案利用对象的形状来构建合成模式,以进行对象定位。我们的方法的优点在于三个方面:1)所提出的方法对正面图像内容变化具有鲁棒性,并且不依赖于单个图像进行识别和定位。 2)模式匹配方案对对象透视变换具有鲁棒性; 3)该方法对杂乱环境引入的噪声不敏感,例如不平衡的照明和反射。为了评估所提出的方法,我们在实际应用环境中对其进行了测试。大规模实验表明了我们方法的准确性和鲁棒性。

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