A Simple Graph Theoretic Approach for Object Recognition

S. Hingway, K. Bhurchandi
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引用次数: 4

Abstract

An image can be stored as a graph which requires very less memory for the storage. A graph is pictorial representation of a finite relation between the entities with help of nodes and edges. Edges connect the nodes whenever the nodes are related. For converting an image into a graph, it is first converted to a binary format. Binary image is converted to a skeleton form which preserves the shape details efficiently. Skeleton is then converted to a shock graph which has structure like a tree. The hierarchy of nodes in the graph structure is decided by a Shock Graph Grammar. Binary images with different shapes have different skeletons and different tree structure. Number of features of the graph can be extracted which facilitate comparison of shapes using these features. Comparison of shapes using their Shock graphs provides a very effective way of object recognition. A graph can be divided into sub graphs. An object recognition frame work by comparing the sub graphs has been presented here.
对象识别的简单图论方法
图像可以存储为图形,这需要非常少的存储内存。图是借助节点和边来表示实体之间有限关系的图形表示。当节点相关时,边连接节点。要将图像转换为图形,首先要将其转换为二进制格式。将二值图像转换为骨架形式,有效地保留了图像的形状细节。然后将骨架转换为具有树状结构的激波图。图结构中节点的层次由震荡图语法决定。不同形状的二值图像具有不同的骨架和不同的树形结构。可以提取图形的特征数量,便于使用这些特征对形状进行比较。使用激波图进行形状比较提供了一种非常有效的对象识别方法。图可以分成子图。通过比较子图,给出了一个目标识别框架。
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