Dipartimento di Ingegneria dell'Informazione, Università degli Studi di Modena e Reggio Emilia, Emilia 41125, Italy.
IEEE Trans Image Process. 2010 Jun;19(6):1596-609. doi: 10.1109/TIP.2010.2044963. Epub 2010 Mar 11.
In this paper, we define a new paradigm for eight-connection labeling, which employs a general approach to improve neighborhood exploration and minimizes the number of memory accesses. First, we exploit and extend the decision table formalism introducing OR-decision tables, in which multiple alternative actions are managed. An automatic procedure to synthesize the optimal decision tree from the decision table is used, providing the most effective conditions evaluation order. Second, we propose a new scanning technique that moves on a 2 x 2 pixel grid over the image, which is optimized by the automatically generated decision tree. An extensive comparison with the state of art approaches is proposed, both on synthetic and real datasets. The synthetic dataset is composed of different sizes and densities random images, while the real datasets are an artistic image analysis dataset, a document analysis dataset for text detection and recognition, and finally a standard resolution dataset for picture segmentation tasks. The algorithm provides an impressive speedup over the state of the art algorithms.
在本文中，我们定义了一个新的八连接标记范例，该范例采用了一种通用方法来改进邻域探索并最小化内存访问次数。首先，我们利用并扩展了决策表形式化引入或决策表，其中管理多个替代操作。使用自动过程从决策表合成最优决策树，提供最有效的条件评估顺序。其次，我们提出了一种新的扫描技术，在图像上以 2x2 像素网格移动，该技术由自动生成的决策树进行优化。我们提出了与现有方法的广泛比较，包括合成数据集和真实数据集。合成数据集由不同大小和密度的随机图像组成，而真实数据集是一个艺术图像分析数据集、一个用于文本检测和识别的文档分析数据集，最后是一个用于图片分割任务的标准分辨率数据集。该算法在速度上相对于现有算法有显著的提升。
