[1]张芝齐,吴建平,钱文华,等.一种基于旋转不变性的纹理粗糙度改进算法[J].计算机技术与发展,2018,28(11):65-68.[doi:10.3969/ j. issn.1673-629X.2018.11.015]
　ZHANG Zhi-qi,WU Jian-ping,QIAN Wen-hua,et al.An Improved Texture Coarseness Algorithm Based on Rotation Invariant[J].,2018,28(11):65-68.[doi:10.3969/ j. issn.1673-629X.2018.11.015]
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一种基于旋转不变性的纹理粗糙度改进算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年11期
页码:
65-68
栏目:
智能、算法、系统工程
出版日期:
2018-11-10

文章信息/Info

Title:
An Improved Texture Coarseness Algorithm Based on Rotation Invariant
文章编号:
1673-629X(2018)11-0065-04
作者:
张芝齐1; 吴建平1; 2; 3; 钱文华1; 陈培德1; 2; 3
1. 云南大学 信息学院,云南 昆明 650500; 2. 云南大学 云南省电子计算中心,云南 昆明 650223; 3. 云南省高校数字媒体技术重点实验室,云南 昆明 650223
Author(s):
ZHANG Zhi-qi1; WU Jian-ping1; 2; 3; QIAN Wen-hua1; CHEN Pei-de1; 2; 3
1. School of Information,Yunnan University,Kunming 650500,China; 2. Electron &Computer Center of Yunnan Province,Yunnan University,Kunming 650223,China; 3. Digital Media Technology Key Laboratory of Universities and Colleges in Yunnan Province,Kunming 650
关键词:
纹理粗糙度; 旋转不变性; 量化精度; 领域均值差值; 分式量化
Keywords:
texture coarseness; rotation invariant; quantization precision; field mean difference; fractional quantization
分类号:
TP301.6
DOI:
10.3969/ j. issn.1673-629X.2018.11.015
文献标志码:
A
摘要:
少数民族图案纹理粗糙度的提取对少数民族图案的表达和解析提供了有效的数据支撑,也对少数民族图案的合成提供了相应的特征信息。针对原 Rosenfeld 纹理粗糙度算法的量化精度不高和其计算结果旋转不变性不稳定,同时为了适应在不同角度下稳定准确地提取少数民族图案纹理粗糙度的需要,提出了一种基于领域均值差值和分式量化的改进算法。用数学理论推导、证明了分式量化的量化精度为最高,通过计算在不同角度下提取一张少数民族图案的纹理粗糙度的方差来衡量该算法的旋转不变性。结合 Brodatz 纹理图像库和苗族刺绣图案库进行了 Matlab 算法验证实验,实验数据对比结果表明,改进算法旋转不变性得到了显著提高。
Abstract:
Minority pattern texture roughness extraction provides effective data to support the minority pattern texture and also the corresponding feature information on the synthesis of minority pattern. In the light of the low accuracy of the original Rosenfeld texture coarseness algorithm and the unstable rotation invariant of the results and at the same time in order to adapt to the need of extracting the roughness of the minority pattern and texture steadily and accurately at different angles,we propose an improved algorithm based on field mean difference and pattern of fractional quantization. It is proved that the fractional quantization accuracy is the highest. The rotation invariance of the improved algorithm is measured by calculating the variance of the texture roughness of a minority pattern at different angles.Combined with Brodatz texture image database and the Miao nationality embroidery pattern,it proves the rotation invariant through Matlab simulation experiment. The simulation shows that the improved algorithm has greatly improved in rotation invariant.

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更新日期/Last Update: 2018-11-10