Local Binary Quaternion Rotation Pattern for colour texture retrieval

Author(s):  
Hela Jebali ◽  
Noel Richard ◽  
Mohamed Naouai
Author(s):  
I.V. TORBINA ◽  
◽  
I.R. FARDEYEVA ◽  

The paper assesses the promising varieties of winter wheat in a competitive variety test by the main economic and biological characteristics that determine the suitability of the variety for commercial use. The object of research was the authors’ own breeding material. The experiments on the selection of winter wheat were made in the experimental crop rotation pattern of the Institute.


2012 ◽  
Vol 263-266 ◽  
pp. 167-170 ◽  
Author(s):  
Xin Wu Chen ◽  
Jing Ge ◽  
Jin Gen Liu

Contourlet transform is superior to wavelet transform in representing texture information and sparser in describing geometric structures in digital images, but lack of robust character of shift invariance. Non-subsampled contourlet transform (NSCT) alleviates this shortcoming hence more suitable for texture and has been studied for image de-noising, enhancement, and retrieval situations. Focus on improving the retrieval rates of existing contourlet transforms retrieval systems, a new texture retrieval algorithm was proposed. In the algorithm, texture information was represented by four statistical estimators, namely, L2-energy, kurtosis, standard deviation and L1-energy of each sub-band coefficients in NSCT domain. Experimental results show that the new algorithm can make a higher retrieval rate than the combination of standard deviation and energy which is most commonly used today.


Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1828
Author(s):  
Xiaoxuan Wei ◽  
Yansu Li ◽  
Xiaoguang Fan ◽  
Chaoxing He ◽  
Yan Yan ◽  
...  

The tremendous scale of protected vegetable cultivation incidentally produces considerable vegetable residue, which refers to the remaining parts of plants after the final harvest. The low use rate of vegetable residue results in nutrient waste and environmental pressure in China. In this study, we put forward vegetable residue directly returned to the soil and investigated its feasibility. Residue return was steadily conducted 5 times in a Chinese solar greenhouse with the cucumber–tomato rotation pattern. Results showed that residue return increased the soil alkali-hydrolysed nitrogen and available potassium contents by 4.97–26.22% and 9.31–21.92%, respectively, along with slightly reduced soil pH and bulk density by 1.00–5.39% and 6.72–11.81%, respectively. Gemmatimonadetes, Firmicutes, Acidobacteria, Basidiomycota, and Mortierellomycota were the major phyla with noticeable changes when residue return was conducted 5 times. Fruit yield began to obtain remarkable increase by 5.81–9.26 t·ha−1 after residue return was conducted 3 times, bringing about additional profits of 5382.0–8519.2 USD·ha−1. Residue return could cut down the disposal expense of vegetable residues by 480.89 USD·ha−1. Moreover, residue return could supplement nutrients to soil, potentially contributing to reducing chemical fertilizer inputs. In conclusion, in situ vegetable residue return could be considered to be a feasible and sustainable use technique for vegetable residues in the Chinese solar greenhouse.


Author(s):  
Susana Alvarez ◽  
Anna Salvatella ◽  
Maria Vanrell ◽  
Xavier Otazu

Author(s):  
Girish Katkar ◽  
Pravin Ghosekar

The TEXRET-System, a texture retrieval system based on soft-computing technologies is being developed. The importance of this kind of system is increasing due to the massive access to digital image databases, which also demand the existence of systems that can understand human high-level requests. The TEXRET system has the following features: (i) direct access from the Internet, (ii) high interactivity, (iii) texture retrieval using human-like or fuzzy description of the textures, (iv) content-based texture retrieval using user-feedback, and (v) synthesis or generation of the requested textures when these are not found in the database, which allows a growing of the database. One of the main system features is synthesis of the requested textures when these are not found in the database, which allows a growing of the database. Missing textures are synthesized interactively using Markov Random Fields and interactive genetic algorithms. This paper is centered on the texture synthesis of the textures.


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