Analysis of Dot Micro-Morphology for Image Replication Quality Evaluation
Dot is the smallest structural unit of image printing. Micro-characteristic of each printing dot such as spreading area, dot shape and three-dimensional shape which are formed on the surface of substrates affect the image replication quality directly. It is significant to accurately extract and analyze dot microstructure in the process of image transfer for evaluating the quality of image replication .Different shapes of printing dots from the standard offset proof are extracted through microscopic test system. The optimal threshold segmentation algorithm was determined by experiment which gets accurate microscopic quantitative value of the dot, the obtained two-dimensional and three-dimensional shape of printing dot became the basis to evaluate the quality of image replication. The between-cluster variance method is used for dot image segmentation. The research was carried on to track image edge after image threshold and to extract the characteristic parameters to accurately characterize the two-dimensional shape, thus characterizing the image replication quality of dot plane form accordingly; on the basis of collected dot two-dimensional data, the experiment was conducted to combine with gray value differences of single dot caused from ink accumulation within its shape areas. Besides, dot density contour and three-dimensional data were quantized by programming in order to restore three-dimensional shape of printing dot on the surface of substrates quantitatively and intuitively. It shows that quality of dot micro-morphology is the fundamental guarantee of image replication quality. The changes of dot shape, area as well as three-dimensional shape in the process of image replication affect the printing quality. Extraction and analysis dot microstructure can detect dot replication quality intuitively which becomes new method to evaluate image replication quality.
Ouyang Yun, Xu Min, Yang Li and Liu Xunting
Q. Wang et al., "Analysis of Dot Micro-Morphology for Image Replication Quality Evaluation", Applied Mechanics and Materials, Vol. 731, pp. 135-140, 2015