| 一种基于图像灰度直方图相似度计算的室内定位方法 |
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| 引用本文： | 王永康,汪云甲,毕京学,曹鸿基.一种基于图像灰度直方图相似度计算的室内定位方法[J].测绘通报,2018,0(4):63-67. |
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| 作者姓名： | 王永康 汪云甲 毕京学 曹鸿基 |
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| 作者单位： | 中国矿业大学环境与测绘学院, 江苏 徐州 221116 |
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| 基金项目： | 国家重点研发计划(2016YFB0502102) |
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| 摘 要： | 近年来，视觉定位由于定位精度高广泛应用于室内定位与导航。然而，室内环境复杂多变，视觉定位在很多场景下无法实现高精度定位，而且多数视觉定位算法耗时和计算复杂度高，不适用于智能手机。为实现基于智能手机的准确高效定位，本文提出了一种基于图像灰度直方图相似度计算的定位方法。该方法分为两个阶段：离线阶段和在线阶段。离线阶段在已知坐标的格网点分别利用智能手机采集图像，提取图像灰度直方图，建立图像灰度直方图图像特征库；在线阶段智能手机在待测点采集图像提取灰度直方图，然后与图像特征库进行相似度计算，选取相似度和最大值的格网作为概略位置，以相似度为权重采用加权均值法得到准确位置。将所提方法和KNN算法进行对比，试验结果表明，该方法的平均定位误差优于0.3 m，与KNN算法相比定位精度提高了40.7%，计算时间优于1.7 s。
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| 关 键 词： | 室内定位 灰度直方图 图像特征库 相似度计算 加权均值 |
| 收稿时间： | 2017-07-24 |
The Method of lndoor Positioning Based on Similarity Computation of Image Gray Histogram |
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| WANG Yongkang,WANG Yunjia,BI Jingxue,CAO Hongji.The Method of lndoor Positioning Based on Similarity Computation of Image Gray Histogram[J].Bulletin of Surveying and Mapping,2018,0(4):63-67. |
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| Authors: | WANG Yongkang WANG Yunjia BI Jingxue CAO Hongji |
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| Institution: | China University of Mining and Technology School of Environment Science and Spatial Informatics, Xuzhou 221116, China |
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| Abstract: | In recent years,visual positioning is widely used in indoor positioning and navigation because of its high positioning accuracy.However,we can't achieve high-precision positioning in many scenes with visual positioning algorithms due to complex indoor environment,and most of the visual positioning algorithms are not suitable for smartphones for its' high time and computational complexity.In order to realize the accurate and efficient positioning with smartphones,a method based on similarity computation of gray histogram is proposed.The method is divided into two stages:the offline stage and the online stage.In the offline stage,we acquire the image in the grid points of the known coordinates with the smartphone,and then the gray histogram of the image is extracted to establish the image gray histogram image feature database;In the online stage,the image is collected and gray histogram is extracted on test point by the smartphone,and then calculate the similarity between it and the image feature database.The grid of similarity and maximum is selected as the approximate position,the similarity is used as the weight,and the exact location is obtained by weighted mean method.Compare the proposed method with the KNN algorithm,the experimental result shows that the average positioning error is less than 0.3 m,average point positioning accuracy of this method is better than that of KNN algorithm,and compared to the KNN algorithm,the positioning accuracy is improved by 40.7%,and the computing time is better than 1.7 s. |
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| Keywords: | indoor positioning gray histogram image feature database similarity calculation weighted mean |
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