纺织学报 ›› 2011, Vol. 32 ›› Issue (4): 52-56.
• 纺织工程 • 上一篇 下一篇
包晓敏,曹作宝,汪亚明,周砚江,朱寒宇
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摘要: 提出了一种基于嗅觉神经网络的织物组织识别的新方法。在生物嗅觉神经网络建模技术的基础上,根据激励响应关系来调节KIII模型输入电压。然后将采集的织物图像在x和y方向投影,计算其组织点大小,然后重排组织点,将重排结果运用上述经过参数调节的KIII模型识别。样本数据验证表明:所建的模型对平纹组织,缎纹组织识别率都高于未调节参数的KIII模型,而对斜纹组织在采用新的组织点提取模型后,识别率也有明显的提高。
Abstract: According to the stimulus-response relationship regulate the input voltage of the KIII model, based on the biological olfactory neural network model technology. And then project the collected fabric image in the direction of x and y, calculated the size of the fabric point, and then rearrangement fabric point. Images are trained by the neural network after processing above-mentioned. The experiment results show that the improved network is effective, and the method can accurately extract the fabric points and it is better than the traditional methods. A new method to extract the fabric points is presented for the twill stitch, the improved network also is effective.
包晓敏;曹作宝;汪亚明;周砚江;朱寒宇. 基于嗅觉神经网络的织物组织识别[J]. 纺织学报, 2011, 32(4): 52-56.
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