Objective To extract handwritten text information from the express lists using the H-Cb color mixing model without the effect of illumination conditions. Methods Firstly, the image was converted from RGB color space to HSI color space and the YCbCr color space. Then the Cb color component of the improved YCbCr color space was combined with the H color component of the HSI color space. Finally, threshold processing and inverse processing were conducted on the extracted handwritten text information. The extracting results of this algorithm were compared with the threshold segmentation using Cb color components of the YCbCr color space and handwritten text clustering algorithm based on Lab color space in terms of segmentation results and character recognition rate. Results The handwritten text detected using the H-Cb mixed color model was more accurate, and had a higher recognition rate. Under the conditions of ideal character segmentation, the recognition rate reached up to 96% . Conclusion Using H-Cb mixed color model to extract handwritten text could avoid the effect of illumination conditions, and the extracted image had few noises and high recognition rate, and this algorithm was simple and feasible, which provided support for the detection and decision technology of color image.