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Regions Labeling in Outdoor Scene Images

机译:地区在户外场景图像中标记

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摘要

Outdoor scene analysis is a complex problem for both image processing and pattern recognition domains. This paper proposes an approach for labeling regions in outdoor scene images. The basic idea of this approach is to label local image regions into semantic objects such as tree, sky and road etc. There are four phases in the approach: segmentation, feature extraction, region labeling and merging. Firstly, modified Marker-Controlled Watershed (MCWS) algorithm proposes for segmented regions generation. And then, color feature extracted from segmented regions are given as input to 3-layer Artificial Neural Network (ANN) classifier for labeling. Finally, region merging is performed if the two regions are adjacent with the same color values. The proposed method is test on our real scene image dataset which are collected from our university campus.
机译:户外场景分析是图像处理和模式识别域的复杂问题。 本文提出了一种在户外场景图像中标记区域的方法。 这种方法的基本思想是将本地图像区域标记为树木,天空和道路等语义对象等。方法中有四个阶段:分段,特征提取,区域标记和合并。 首先,修改的标记控制流域(MCWS)算法提出了分段区域的生成。 然后,从分段区域提取的彩色特征作为用于标记的3层人工神经网络(ANN)分类器的输入。 最后,如果两个区域与相同的颜色值相邻,则执行区域合并。 所提出的方法是在我们的真实场景图像数据集上测试,该数据集从我们的大学校园收集。

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