Image Quality Evaluation of Knitted Glove Contour Segmentation
In order to achieve more efficient and accurate contour segmentation of solid colored gloves,this paper constructs a knitted glove image quality evaluation index based on image grayscale histogram feature parameters with contour segmentation as the objective.By shooting glove images of different quality levels,the relationship between the shape of grayscale histograms and the difficulty of segmenting contours is analyzed.An image quality evaluation model composed of peak value,valley value,peak distance,and intra class variance in grayscale histograms is summarized.This model can quantitatively calculate image indicators,which are the basis for automatic shooting and parameter adjustment.The experimental results show that the evaluation index values solved by the model have good consistency with the subjective evaluation level of the human eye,and the evaluation index values are independent of the color of the gloves themselves,indicating good universality.Therefore,the completed evaluation indicators can change the manual parameter adjustment shooting method that relies on human eye observation,providing an adjustment basis and foundation for intelligent camera parameter adjustment shooting required for online detection.
NETL
NSTL
万方数据
