Piece goods blemish detecting method based on morphological analysis

Abstract

The invention discloses a piece goods blemish detecting method based on morphological analysis. The piece goods blemish detecting method comprises the steps that a line-scan digital camera is used for conducting image collection on piece goods in motion, the distance of adjacent tissue points of the piece goods is obtained by conducting basic brightness stretching and binaryzation processing on gray level images of the piece goods, and the distance serves as the reference value of the size of structural elements; then, morphological close operation is conducted, filling is conducted on common weaving point gaps, the number of the weaving points at a blemish position is small and the weaving points at the blemish position are irregular, so that the weaving points stand out in brightness; at least, binaryzation processing is conducted on the images, determining of the threshold of the images is controlled through gamma training selecting of gray level power transform, blemished binary images are counted and marked, blemish information is output, and the blemish detecting process of the piece goods is completed. The piece goods blemish detecting method based on morphological analysis is more accurate and simpler in structure, and improves the calculation speed; can weaken the interference of background brightness unevenness; brings convenience to realization of automatic detection.

Description

technical field [0001] The invention relates to a fabric detection method, in particular to a cloth defect detection method, in particular to a cloth defect detection method based on morphological analysis. Background technique [0002] In the textile production process, quality control and testing are very important, and cloth defect detection is a particularly critical part of it. At present, the detection method of most textile enterprises is still manual detection. This method has a low detection speed and is easily affected by the subjective factors of the inspectors. False detections and missed detections often occur, and domestic labor costs are getting higher and higher. Therefore, manual detection is increasingly unable to meet the requirements of modern manufacturing enterprises. Replacing manual detection with advanced automatic detection technology can improve detection efficiency, reduce labor force, reduce labor intensity and further improve the quality of clo...

AI Technical Summary

Problems solved by technology

Among them, the commonly used detection algorithm is based on the method of spectral analysis or combined with other methods. These methods extract relevant feature information through the conversion between the space domain and the frequency domain, but the method involving the frequency domain has a large amount of calculation and the conversion between domains. Make it difficult to guarantee the accuracy of some information

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