基于视觉显著性的织物起球客观等级评价

Fabric Pilling Objective Evaluation Based on Visual Saliency

传统的主观织物起球等级评价容易受检验人员经验、心理等因素影响,难以满足准确评价起球等级的需要。在分析视觉显著性机制的基础上,提出一种基于视觉显著性的织物起球等级客观评价新方法。首先利用小波多层静态分解以及各子图之间选择性的中央-周边操作,提高织物起球的近似、水平及垂直细节信息的显著度;在此基础上,通过差分子图融合形成织物起球显著图。然后,根据织物起球特征所确定的阈值分割出织物起球兴趣区。最后,从兴趣区提取织物起球特征,并通过BP(back propagation)人工神经网络进行起球疵点客观等级评价。试验结果表明,该方法能够有效地进行织物起球疵点客观等级评价,并且具有较强的抗噪声能力。

The subjective evaluation of fabric pilling grade is easily affected by the traditional inspection based on personnel experience, psychology and other factors, which is difficult to meet the accurateness of the pilling grade evaluation. With the analysis of visual saliency mechanism, a new objective evaluation method of fabric pilling grade was put forward. Firstly, the approximate, horizontal detail and vertical detail information saliency about fabric pilling were improved by using wavelet static multi- decomposition and central-surround operation of the selectivity among sub-images. Based on this, the fabric pilling saliency map was formed through the difference sub-images fusion. Then, the fabric pilling of interest region was determined by threshold according to the fabric pilling characteristic. Finally, extract pilling features from the interest region, and fabric pilling was evaluated objectively by the BP （back propagation） artificial neural network. The test results show that this method can make an objective evaluation for pilling grades effectively, which have a strong anti-noise capacity.