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Application of the Fundamental Solution Method to Object Recognition in the Pictures

机译:基本解法在图片目标识别中的应用

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Recognition of objects in pictures and movies requires the use of techniques, such as filtering, segmentation and classification. Image filtering is required to remove all artifacts that hinder the unequivocal identification and sharpen interesting objects. Segmentation refers to finding areas of images respected to individual objects. For the selected areas corresponding to objects in the selected picture, the classification of objects finally gives information about the type of object which orientation is made. This paper presents a method for the classification of objects from drawings as a bitmap using the method of fundamental solutions (MFS). The MFS was tested on the selected bitmap depicting simple geometric shapes. The correlations between errors occurring on the boundary for particular shapes are used for the selection of geometric shape figures. Due to this correlation, it is possible to recognize the shape of the image appearing on the drawing by an analysis consisting of the comparison of recognized points describing the shape of contour to a database containing solutions of boundary value problems for the selected shape. In one way, the comparison of the pattern can determine which shape from database it is most similar to in terms of contour. This article appear that this approach is very simple and clearly. In result, this method can be used to recognition of the objects in the systems of real-time processing.
机译:识别图片和电影中的对象需要使用诸如过滤,分割和分类之类的技术。需要进行图像过滤,以消除所有阻碍明确识别并锐化有趣物体的伪像。分割是指找到与各个对象有关的图像区域。对于与所选图片中的对象相对应的所选区域,对象的分类最终会给出有关进行定向的对象类型的信息。本文提出了一种使用基本解(MFS)方法将图形中的对象分类为位图的方法。在选定的位图上测试了MFS,该位图描述了简单的几何形状。在特定形状的边界上发生的误差之间的相关性用于选择几何形状图形。由于这种相关性,可以通过分析来识别出现在图形上的图像的形状,该分析包括将描述轮廓形状的识别点与包含所选形状的边界值问题解决方案的数据库进行比较。以一种方式,图案的比较可以从轮廓上确定与数据库中最相似的形状。本文看来,这种方法非常简单明了。结果,该方法可用于识别实时处理系统中的对象。

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