Taking advantage of multi-regions-based diagonal texture structure descriptor for image retrieval

2018 ◽  
Vol 96 ◽  
pp. 347-357 ◽  
Author(s):  
Wei Song ◽  
Yubing Zhang ◽  
Fei Liu ◽  
Zhilei Chai ◽  
Feng Ding ◽  
...  
2011 ◽  
Vol 44 (9) ◽  
pp. 2123-2133 ◽  
Author(s):  
Guang-Hai Liu ◽  
Zuo-Yong Li ◽  
Lei Zhang ◽  
Yong Xu

2019 ◽  
Vol 8 (3) ◽  
pp. 3958-3963 ◽  

This research work contributes a system for heterogeneeous medical image retrieval usiing Multi-trend structure descriptor (MTSD) and fuzzy support vector machine (FSVM) classifier. The MTSD encodes the local level structure in the form of trends for color, shape and texture information of medical images. Experimental results demonstrate thatt the fusion of MTSD and FSVM significantly increases the retrieval precision for heterogeneeous medical image dataset. The simplest Manhattan diistance is incorporated for measuring the similarity. The feasibility of thee proposed system is extensively experimented on benchmark daataset and the experimental study clearly demonstrated that proposed fusion of MTSD with Fuzzy SVM gives significantly superior average retrieval precision.


Author(s):  
V. RAMACHANDRAN ◽  
Y. Sowjanya Kumari ◽  
P. Harini

Image retrieval approach by proposing a new image feature detector and descriptor, namely the micro-structure descriptor (MSD). We present a computational model of creative design based on collaborative interactive genetic algorithms. This Paper test our model on floor planning. This Paper guide the evolution of floorplan based on subjective and objective criteria. The subjective criteria consists of designers picking the floorplan they like the best from a population of floorplans, and the objective criteria consists of coded architectural guidelines. The results demonstrate that it is much more efficient and effective than representative feature descriptors, such as Gabor features and multi-textons histogram, for image retrieval.


2016 ◽  
Vol 13 (8) ◽  
pp. 222-230 ◽  
Author(s):  
Meng Zhao ◽  
Huaxiang Zhang ◽  
Lili Meng

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