Data for: Mirror Symmetry Detection in Curves Represented by Means of the Slope Chain Code

Symmetry is an important feature in natural and man-made objects; particularly, mirror symmetry is a relevant task in fields such as computer vision and pattern recognition. In the current work, we propose a new method to characterize mirror-symmetry in open and closed curves represented by means of the Slope Chain Code. This representation is invariant under scale, rotation, and translation, highly desirable properties for object recognition applications. The proposed method detects symmetries through simple inversion, concatenation and reflection operations on the chains, thus allowing the classification of symmetrical and asymmetrical contours. It also introduces a measure to quantify the degree of symmetry in quasi-mirror-symmetrical objects. Furthermore, it allows the identification of multiple symmetry axes and their location. Results show high performances in symmetrical/asymmetrical classification (0.9 recall, 0.9 accuracy, 0.97 precision) and axes’ detection (0.8 recall, 0.84 accuracy, 0.99 precision). Compared to other methods, the proposed algorithm provides properties such as: global, local, and multiple axes’ detection, as well as the capability to classify symmetrical objects, which makes it adequate for several practical applications, like the three exemplified in the paper.

The available demo of the proposed mirror symmetry detection method is written in Matlab.

对称性是自然与人工造物的重要特征；尤为关键的是，镜像对称性在计算机视觉（computer vision）与模式识别（pattern recognition）等领域均为极具研究价值的课题。本研究提出一种全新方法，用于表征基于斜率链码（Slope Chain Code）表示的开放与闭合曲线的镜像对称性。该表示方法具备尺度（scale）、旋转（rotation）与平移（translation）不变性，这正是目标识别应用中极具实用价值的特性。所提方法通过对链码执行简单的反转（inversion）、拼接（concatenation）与反射（reflection）操作实现对称性检测，进而可完成对称与非对称轮廓的分类任务。此外，该方法还提出一种量化准镜像对称物体对称程度的指标，同时可识别多条对称轴及其位置。实验结果表明，其在对称/非对称分类任务中表现优异（召回率（recall）0.9、准确率（accuracy）0.9、精确率（precision）0.97），在对称轴检测任务中同样表现出色（召回率（recall）0.8、准确率（accuracy）0.84、精确率（precision）0.99）。与其他方法相比，所提算法具备全局、局部与多对称轴检测能力，同时可完成对称物体的分类任务，因此可适用于多种实际应用场景，正如本文中列举的三个案例所示。
本研究所提镜像对称性检测方法的可用演示程序采用Matlab语言编写。