This work aims to propose a character printing quality inspection method based on multi-object matching and fusion character features, to enhance the robustness and recognition of character registration to changes in character pose, as well as print quality inspection accuracy and defect type analysis for different character products. Firstly, multiple qualified character sample images were applied to template construction. Then the multi-object matching method was introduced to match the characters to be inspected to eliminate the effect of changes in character pose on character registration. Then a pixel-by-pixel comparison was performed to verify the quality of the character area. Last, with gray threshold segmentation and Sobel edge detection, the character region was divided into three local feature regions to be tested: edge, foreground, and background. Significant character features such as edge integrity, area and gray scale of foreground and background were collected. The adaptive qualifying range for each feature was trained from multiple character samples. The type of defect was given with the fused character features. Experimental results show that, when it came to different types of character products with different precision requirements, the accuracy of the proposed method for character quality was 100%, and the accuracy of classification of defect types remained above 84.2%. Featured by good robustness and adaptability, the proposed character quality inspection method has good application value in packaging, printing and other industries.