کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
528790 869608 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An aerial image recognition framework using discrimination and redundancy quality measure
ترجمه فارسی عنوان
چارچوب تشخیص تصویر هوایی با استفاده از تبعیض و اندازه گیری کیفیت افزونگی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• Aerial image categorization framework.
• Discriminative subgraphs.
• Subgraph mining.
• SVM.

Aerial image categorization plays an indispensable role in remote sensing and artificial intelligence. In this paper, we propose a new aerial image categorization framework, focusing on organizing the local patches of each aerial image into multiple discriminative subgraphs. These meaningful subgraphs reflect both the geometric property and the color distribution of an aerial image. First, each aerial image is decomposed into a collection of regions in terms of their color intensities. Thereby region connected graph (RCG), which models the connection between the spatial neighboring regions, is constructed to encode the spatial context of an aerial image. Second, a novel subgraph mining technique is adopted to discover the frequent structures in the RCGs constructed from the training aerial images. Thereafter, a set of refined structures is selected among the frequent ones toward being highly discriminative and low redundant. Lastly, given a new aerial image, its sub-RCGs corresponding to the refined structures are extracted. They are further quantized into a discriminative vector for SVM classification. Thorough experimental results validate the effectiveness of the proposed method. In addition, the visualized mined subgraphs show that the discriminative topologies of each aerial image are discovered.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 37, May 2016, Pages 53–62
نویسندگان
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