Journal of Geo-information Science >
A Harris Corner Detection Based Evaluation Method for SVG Visualization Conversion Effect
Received date: 2013-08-28
Revised date: 2013-12-11
Online published: 2014-05-10
With the development of mobile communication technologies, the demands of location-based spatial information services are more and more extensive in order for scientists to effectively obtain rich spatial information in mobile internet era anytime and anywhere, and SVG (Scalable Vector graphics) is becoming a hot application on data representation and organization in Location Based Services (LBS). However, few past researches focused on image quality assessment of the conversion from different spatial data format to SVG format. So in this context, according to the unique demand on SVG_based representation and organization for spatial data in LBS, this research put forward the conversion method and quality assessment method from multiple formats to SVG format. Firstly, by using of the directly loaded raster images and by running the vector data conversion programme, a valid conversion is achieved from multi-source spatial data formats to SVG format. Secondly, from the combination of qualitative and quantitative view, the comparison between the image quality before and after the conversion is analyzed. And, based on the design of corner detection index and evaluation processes, a Harris_corner detector method is proposed and verified to evaluate the transform result. The test shows that SVG_based representation is suited for spatial data in LBS, especially for the vector data, and the SVG image after conversion for either raster or vector data has a high image quality. As the JPG raster image is concerned, compared with the original image, the accuracy of the converted SVG image changed little, but the resolution of the converted SVG image is less than the original one. On the other hand, the accuracy and clarity of the converted vector data is similar to the original vector data. And the conversion of raster data is less effective than that of vector data, which shows that the corner detection technique on SVG transform is feasible. Further, it verifies a reliable SVG_based mobile location service information expression and spatial organization model, and helps to popularize and strengthen SVG application in LBS.
WANG Yanhui, LI Yue . A Harris Corner Detection Based Evaluation Method for SVG Visualization Conversion Effect[J]. Journal of Geo-information Science, 2014 , 16(3) : 368 -375 . DOI: 10.3724/SP.J.1047.2014.00368
[1] 李德仁,李清泉,谢智颖,等.论空间信息与移动通信的集成应用[J].武汉大学报信息科学版,2002,27(1):1-6.
[2] Meng L. Egocentric design of map-based mobile services[J]. The Cartographic Journal,2005,42(1):5-13.
[3] 高博,万方杰,宋国民,等.基于位置服务的空间信息传输模型[J].测绘科学技术学报,2009,26(1):12-14.
[4] 石善斌,吕志平.SVG 在移动地图服务中的组织与编码[J].地理信息世界,2009(2):78-83.
[5] Sun H B, Jiang P Y, Yu B, et al. An SVG-based interactive drawing viewing solution for mobile design or manufacturing collaboration[J]. Applied Mechanics and Materials, 2008(10-12):208-212.
[6] 李清泉,谢智颖,左小清,等.基于SVG的空间信息描述与可视化表达[J].测绘学报,2005,34(1):58-63.
[7] 蒋红燕,杨哲海.地理信息从SHP格式向SVG格式的转换[J].测绘通报,2011(2):73-76.
[8] 李东,黄正华.MapInfo 到SVG 的转换图形的自适应显示处理[J].华中科技大学学报(自然科学版),2010,38(12): 9-11.
[9] 王唤良,朱建军.交互式地图绘制与SVG格式文档的生成[J].武汉大学学报(信息科学版). 2011,36(8):995-998.
[10] 谢颖.SVG 技术在WebGIS 和移动GIS 中的应用研究[D].长春:吉林大学,2009.
[11] 陈传波,宋荆汉.基于SVG的实时信息发布优化模型[J]. 计算机工程与科学,2004,26(8):45-47.
[12] Tomokazu F. SVG+Ajax+R: A new framework for Web-GIS.Computational Statistics[J]. Fukuoka Women's University, Fukuoka, Japan, 2007(22):511-520.
[13] 李跃,王艳慧. LBS 中基于SVG的空间数据表达与压缩[J].中国图象图形学报,2011,16(5):903-908.
[14] 李跃.基于SVG的空间数据表达与组织的关键技术研究[D].北京:首都师范大学,2011.
[15] Edward D M, José I F. Architectural impact of the SVG-based graphical components in Web applications[J]. Computer Standards & Interfaces, 2009(31):1150-1157.
[16] 李晖,肖鹏峰,冯学智,等.基于向量场模型的多光谱遥感图像多尺度边缘检测[J].测绘学报,2012,41(1):100-107.
[17] 吴桂平,肖鹏峰,冯学智,等.一种基于频谱段能量的高分辨率遥感图像边缘特征检测方法[J].测绘学报,2011,40 (5):587-562.
[18] Krystian M , Cordelia S. Scale & affine invariant interest point detectors[J]. International Journal of Computer Vision 2004,60(1):63-86.
[19] 赵西安,李德仁.二维对称小波与多尺度影像边缘特征提取[J].测绘学报,2003,32(4):313-319.
[20] 赵文彬,张艳宁.角点检测技术综述[J].计算机应用研究, 2006,23(10):17-19.
[21] 赵万金,龚声蓉,刘纯平,等.一种自适应的Harris 角点检测算法研究[J].计算机工程,2008,10(5):212-215.
[22] 沈士喆,张小龙,衡伟.一种自适应阈值的预筛选Harris 角点检测方法[J].数据采集与处理,2011,26(2):207-213.
/
| 〈 |
|
〉 |