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

机译:自动药房清单准确医学定位的模式匹配方案

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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环境,即药箱的随机面对照相机根据架子上的话。这对传统的基于图像内容的对象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盒本地化框架。代替使用取决于图像内容的特征点或纹理方法,该方法采用模式匹配方案,该方案利用对象的形状来构建合成模式,用于对象本地化。我们的方法的优越性位于三倍:1)所提出的方法对前图像内容变化具有鲁棒性,并且不依赖于单幅图像来进行识别和本地化; 2)模式匹配方案对于对象透视变换是强大的; 3)该方法对杂波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测试它。大规模实验显示了我们方法的准确性和稳健性。

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