A Novel Quality Detection Approach for Non-mark Printing Image
| Autor: | Minfen Shen, Bin Li, Qiong Zhang, Haihong Shen |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Matching (statistics)
Image quality Computer science business.industry Machine vision Fast speed media_common.quotation_subject 0211 other engineering and technologies 02 engineering and technology 021001 nanoscience & nanotechnology Image (mathematics) Software Robustness (computer science) 021105 building & construction Quality (business) Computer vision Artificial intelligence 0210 nano-technology business media_common |
| Zdroj: | Communications in Computer and Information Science ISBN: 9789811039683 GRMSE (2) |
| DOI: | 10.1007/978-981-10-3969-0_20 |
| Popis: | In printing business, a lot of printing products have no apparent marks for registration, which cause the difficulty of printing image quality auto-detection. Aiming to this problem, a novel quality detection approach for non-mark printing image is proposed in this paper. The proposed approach mainly consists of the region feature based registration region selection and fast shape-based image matching method and an improved difference matching method to detect the printing defects. The proposed approach is realized by the well-known machine vision software HALCON. The experiment results show that the proposed approach can detect the printing defects efficiently with high accuracy, fast speed and strong robustness. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|