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The Object Detection and Extraction of Surface Features in Real Scene Image

Author: GaoLiang
Tutor: XuGang
School: North China Electric Power University (Beijing)
Course: Signal and Information Processing
Keywords: Virtual image Extraction of Buildings Road Extraction Waters extracted
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 63
Quote: 0
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Abstract


With the development of remote sensing technology , research MAIN OBJECT real image object detection and extraction in the national economic construction and national defense construction has important academic value and application prospects . This paper studies the real image in Google Earth feature object detection and extraction technologies , mainly to extract objects as buildings, roads , and the waters three types of important information of features . For detection and extraction of buildings with green vegetation index image preprocessing , to remove the interference of the vegetation in the image , and then make use of the watershed algorithm for regional growth , combined with the prior knowledge of the building , and mathematical morphology processing to extract the buildings potential areas . Simultaneous extraction of the shaded area of the building , adjacent buildings and their shadows according to the characteristics of the object-relational features , excluding roads, squares and other non-building area , building area . For the detection and extraction of road vegetation index algorithm for image preprocessing , the dual threshold OSTU and local grayscale consistency algorithm for image segmentation and image merge split , then the combined image shape index validation , finally, the morphological processing to remove noise, to obtain the boundary of the road . Mainly use waters detection and extraction the threshold neighborhood algorithm to obtain the initial outline of the water's edge , and then combined with the shape index denoising preliminary extraction results , and finally the use of mathematical morphology processing waters boundary , eliminating water vessels objects . Finally, images of buildings , roads and waters through select real images of different types of structures use this method to experiment and experimental results indicates the proposed algorithm can better detect and extract these surface features information reached research purposes .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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