基于朝向对比度的无监督边界检测算法

An unsupervised boundary detection algorithm based on orientation contrast model

针对网络上大规模图像集,没有真实标定边界或者获取成本较大,提出了基于朝向对比度的无监督边界检测算法;在朝向对比度的计算上,考虑了多个方向的差异.特别地,该模型尤其适合于检测自然纹理环绕的对象的边界.在Rug标准数据库上的测试结果表明,提出的算法优于当前最好的无监督边界检测算法,验证了该模型的有效性.

For large image sets on the Web, due to the absense of a ground truth boundary or the high cost of getting one, an unsupervised boundary detection algorithm based on orientation contrast model was proposed. The model is especially suited for detecting object boundaries surrounded by natural textures. In the Rug image database, the algorithm outperforms the state-of-the-art unsupervised boundary detection algorithm, which verifies the validity of the model.