Hybrid Features of Tamura Texture and Shape-Based Image Retrieval

被引:1
作者
Pal, Naresh [1 ]
Kilaru, Aravind [3 ]
Savaria, Yvon [2 ]
Lakhssassi, Ahmed [1 ]
机构
[1] Univ Quebec Outaouais, Comp Sci & Engn Dept, Gatineau, PQ, Canada
[2] Ecole Polytech Montreal, Comp Sci & Engn Dept, Montreal, PQ, Canada
[3] Manipal Univ Jaipur, Comp Sci & Engn Dept, Jaipur, Rajasthan, India
来源
RECENT FINDINGS IN INTELLIGENT COMPUTING TECHNIQUES, VOL 3 | 2018年 / 709卷
基金
加拿大自然科学与工程研究理事会;
关键词
CBIR; Image retrieval; Image indexing; Tamura texture features;
D O I
10.1007/978-981-10-8633-5_59
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Search and retrieval of digital images from huge datasets has become a big problem in modern, medical, and different applications. Content-based image recovery (CBIR) is considered as the best solution for automatic retrieval of images. In such frameworks, in the ordering calculation, a few components are separated from each photo and put away as a record vector. Tamura surface features are applied on digital image and registered the low request measurements from the changed image. The separated surface components of the digital image are used for retrieval. These component mixes incorporate the pixels spatial appropriation data into numerical esteem values. The results demonstrate that this strategy is still compelling when the information scale is extensive, and it has predominant versatility than customary indexing strategies.
引用
收藏
页码:587 / 597
页数:11
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