带地网贾卡经编针织物花纹图案的自动识别

带网孔效应的贾卡经编针织物花纹图案曲线复杂，导致织物意匠图的设计耗时费力，为简化这一设计过程，提出一种针对该类贾卡经编针织物花纹图案的自动识别方法。在扫描获取织物图像并预处理后，综合运用Laws纹理能量测量、迭代阈值分割、边缘光滑算法，自动获得织物花纹图案，进而生成意匠图。测试结果表明，这种方法能够有效地去除织物中网孔为图像识别带来的噪音，快速、准确地完成对所需花纹图案的自动识别，生成设计意匠图。识别准确率可达到90%，对于提高该类织物的设计效率具有实用价值。

Automatic identification method of jacquard warp knitted patterns with net

Jacquard warp knitted patterns with net effect have complex curves, leading to the time-consuming design of jacquard patterns. In order to simplify the design process, an automatic identification approach was developed. After scanning fabric and obtaining images and pre-processing, Laws texture energy measurement, iterative threshold segmentation and edge smoothness algorithm were comprehensively used to get the fabric pattern and then generate notation of jacquard design. Test results show that the method can effectively remove the noise for the image recognition caused by the mesh fabric, rapidly and accurately complete the automatic recognition of the required patterns, and then generate the picture of design. Recognition accuracy can reach 90%, which is of practical value to improve the design efficiency of such fabric.