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Color constancy computation for dyed fabrics via improved marine predators algorithm optimized random vector functional-link network
Color Research and Application ( IF 1.4 ) Pub Date : 2021-03-31 , DOI: 10.1002/col.22653
Xiangqi Liu 1, 2 , Donghe Yang 3
Affiliation  

Aiming at the color characteristics of dyed fabrics that are easily affected by changes in light, which affects the correctness of the color difference classification of dyed fabrics, this article proposes the color constancy calculation of dyed fabrics based on improved marine predators algorithm optimized random vector functional-link. First, in order to obtain the excellent initial population of the marine predators algorithm, this article uses two update strategies of the sine and cosine algorithm to screen the randomly initialized population of the marine predators algorithm. Then, the MPA algorithm that initializes the population using the sine and cosine algorithm optimizes the input weights and hidden layer bias parameters of random vector functional-link, thereby improving the prediction accuracy of random vector functional-link. Finally, using the image features extracted by the Gray-Edge framework, the sine and cosine algorithm-marine predators algorithm-random vector functional-link model proposed in this article is used to calculate the color constancy of dyed fabrics, to eliminate the influence of illumination changes on the color difference classification of dyed fabrics. Compared with the other eight algorithms, the dyed fabric image restored by the sine and cosine -marine predators -random vector functional-link algorithm proposed in this article is closest to the image under standard illumination, that is, the color constancy evaluation effect of the dyed fabric is the best.

中文翻译:

通过改进的海洋捕食者算法优化随机向量功能链接网络的染色织物颜色恒常性计算

针对染色织物易受光照变化影响的颜色特性,影响染色织物色差分类的正确性,提出基于改进海洋捕食者算法优化随机向量函数的染色织物颜色恒常性计算。 -关联。首先,为了获得海洋捕食者算法的优秀初始种群,本文采用正弦和余弦算法两种更新策略对海洋捕食者算法的随机初始化种群进行筛选。然后,使用正弦和余弦算法初始化种群的 MPA 算法优化随机向量函数链接的输入权重和隐藏层偏置参数,从而提高随机向量函数链接的预测精度。最后,利用Gray-Edge框架提取的图像特征,采用本文提出的正弦余弦算法-海洋捕食者算法-随机向量泛函-链接模型计算染色织物的颜色恒常性,消除光照变化的影响关于染色织物的色差分类。与其他八种算法相比,本文提出的正弦和余弦-海洋捕食者-随机向量泛函-link算法还原的染色织物图像最接近标准光照下的图像,即颜色恒常性评估效果染色的织物是最好的。采用本文提出的正弦余弦算法-海洋捕食者算法-随机向量泛函-链接模型计算染色织物的颜色恒常性,消除光照变化对染色织物色差分类的影响。与其他八种算法相比,本文提出的正弦和余弦-海洋捕食者-随机向量泛函-link算法还原的染色织物图像最接近标准光照下的图像,即颜色恒常性评估效果染色的织物是最好的。采用本文提出的正弦余弦算法-海洋捕食者算法-随机向量泛函-链接模型计算染色织物的颜色恒常性,消除光照变化对染色织物色差分类的影响。与其他八种算法相比,本文提出的正弦余弦-海洋捕食者-随机向量泛函-link算法还原的染色织物图像最接近标准光照下的图像,即颜色恒常性评价效果染色的织物是最好的。
更新日期:2021-03-31
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