|
Foreign fibers in cotton have serious adverse effects on the quality of textile products, so its effective identification and elimination has important significance and social value. To solve the above problems, we propose a fusion image pretreatment method based on limited contrast adaptive histogram equalization ( CLAHE ) and wavelet analysis ( WT ), The collected cotton polarization images were processed by WT & CLAHE, which effectively improved the contrast of anisotropic fibers in cotton images, and laid the foundation for the rapid and accurate identification of various anisotropic fibers in cotton in the later stage, It laid a foundation for the rapid and accurate identification of all kinds of anisotropic fibers in cotton in the later stage. Compared with manual and systematic detection, the results showed that technical personnel and detection system could accurately detect and identify dead leaves, white paper and color paper without interference from external environment and foreign fiber size. For white wool, hair and mulch film due to similar color or shape is small, technical personnel in the detection is easy to miss, and the detection system in WT & CLAHE image pretreatment, white wool, hair and mulch film detection accuracy is obviously due to artificial detection, especially for the mulch film this is not easy to detect foreign fiber has good recognition effect.
|
