结合邻域信息的场景识别

Minguang Song, Ping Guo
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引用次数: 1

摘要

近年来,人们提出利用人口普查变换直方图的空间主成分分析来识别图像中地点或场景的实例和类别。将PACT与局部差值二值模式(LMBP)相结合,提出了一种新的局部差值二值模式(LDBP),并取得了较好的效果。LDBP是基于中心像素和邻近像素之间的比较。然而,没有考虑相邻像素之间的关系。本文提出了局部相邻二值模式(LNBP)来利用相邻像素之间的关系。LNBP为LDBP提供关于相邻像素的补充信息。我们提出将LDBP与LNBP相结合,使用空间表示进行场景识别。在两个广泛使用的数据集上的实验表明,该方法可以提高识别性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scene Recognition via Combining Information of Neighbors
Recently, spatial principal component analysis of census transform histograms (PACT) was proposed to recognize instance and categories of places or scenes in an image. When combining PACT with Local difference Magnitude Binary Pattern (LMBP), a new representation called Local Difference Binary Pattern (LDBP) was proposed and performed better. LDBP is based on the comparisons between center pixel and its neighboring pixels. However, the relationship among neighbor pixels is not considered. In this paper we proposed Local Neighbor Binary Pattern (LNBP) to utilize the relationship among neighboring pixels. LNBP provides complementary information regarding neighboring pixels for LDBP. We propose to combine LDBP with LNBP, and used a spatial representation for scene recognition. Experiments on two widely used dataset demonstrate the proposed method can improve the performance of recognition.
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