Automatic image segmentation by integrating color-edge extraction and seeded region growing
Automatic image segmentation by integrating color-edge extraction and seeded region growing
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DOI：
10.1109/83.951532
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发表时间：
2001-10-01
影响因子：
10.6
通讯作者：
Aref, WG
中科院分区：
文献类型：
--
作者：
Fan, JP;Yau, DKY;Aref, WG
提出了一种新的图像自动分割方法。该方法首先利用改进的各向同性边缘检测器和快速熵阈值技术自动提取图像的彩色边缘。在所获得的颜色边缘提供了图像中的主要几何结构之后，将这些相邻边缘区域之间的质心作为种子区域生长（SRG）的初始种子。这些种子，然后取代所产生的同质图像区域的质心，通过逐步纳入所需的额外的像素。此外，颜色边缘提取和SRG的结果相结合，提供均匀的图像区域准确和封闭的边界。我们还讨论了我们的图像分割方法的自动人脸检测的应用。此外，语义的人的对象生成的种子区域聚合过程中，将检测到的人脸作为对象种子。
We propose a new automatic image segmentation method. Color edges in an image are first obtained automatically by combining an improved isotropic edge detector and a fast entropic thresholding technique. After the obtained color edges have provided the major geometric structures in an image, the centroids between these adjacent edge regions are taken as the initial seeds for seeded region growing (SRG). These seeds are then replaced by the centroids of the generated homogeneous image regions by incorporating the required additional pixels step by step. Moreover, the results of color-edge extraction and SRG are integrated to provide homogeneous image regions with accurate and closed boundaries. We also discuss the application of our image segmentation method to automatic face detection. Furthermore, semantic human objects are generated by a seeded region aggregation procedure which takes the detected faces as object seeds.