Detection of Pavement Region with Structural Patterns through Adaptive Multi-Seed Region Growing

Sunhee Weon, Sung-Il Joo, Hyeon-Suk Na, Hyung-Il Choi
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引用次数: 2

Abstract

In this paper, we propose an adaptive pavement region detection method that is robust to changes of structural patterns in a natural scene. In order to segment out a pavement reliably, we propose two step approaches. We first detect the borderline of a pavement and separate out the candidate region of a pavement using VRays. The VRays are straight lines starting from a vanishing point. They split out the candidate region that includes the pavement in a radial shape. Once the candidate region is found, we next employ the adaptive multi-seed region growing(A-MSRG) method within the candidate region. The A-MSRG method segments out the pavement region very accurately by growing seed regions. The number of seed regions are to be determined adaptively depending on the encountered situation. We prove the effectiveness of our approach by comparing its performance against the performances of seed region growing(SRG) approach and multi-seed region growing(MSRG) approach in terms of the false detection rate.
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基于自适应多种子区域生长的路面区域结构模式检测
本文提出了一种对自然场景中结构模式变化具有鲁棒性的路面区域自适应检测方法。为了可靠地分割路面,我们提出了两步方法。我们首先检测路面的边界,并使用vray分离出路面的候选区域。雷线是从消失点开始的直线。他们将候选区域分成放射状,包括人行道。一旦找到候选区域,我们将在候选区域内采用自适应多种子区域生长(A-MSRG)方法。A-MSRG方法通过种植种子区域非常准确地分割出路面区域。种子区域的数量将根据遇到的情况自适应地确定。通过将该方法与种子区域生长(SRG)方法和多种子区域生长(MSRG)方法在误检率方面的性能进行比较,证明了该方法的有效性。
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