Region Based Image Retrieval Using Integrated Color, Texture and Shape Features

被引：5
|
作者：
Shrivastava, Nishant [1 ]
Tyagi, Vipin [1 ]
机构：
[1] Jaypee Univ Engn & Technol, Guna 473226, Madhya Pradesh, India
来源：
INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2 | 2015年 / 340卷
关键词：
Region codes; Local binary pattern; Relative location; LOCATION;
D O I：
10.1007/978-81-322-2247-7_32
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper a region based image retrieval scheme has been proposed based on integration of color, texture and shape features using local binary patterns (LBP). The color and texture features are extracted using LBP histograms of quantized color image and gray level images respectively. For improving the discrimination power of LBP, threshold computed using both centre pixel and its neighbors is used. Finally, shape features are computed using the binary edge map obtained using Sobel edge detector from each block. All three features are combined to make a single completed binary region descriptor (CBRD) represented in the LBP way. To support region based retrieval a more effective region code based scheme is employed. The spatial relative locations of objects are also considered to increase the retrieval accuracy.
引用
收藏
页码：309 / 316
页数：8
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