The work aims to enhance the description ability of trademark retrieval technology for trademark features and improve its retrieval accuracy and robustness under external interference. A trademark retrieval algorithm based on the adaptive combination of color and space features was proposed. Firstly, the dominant color descriptor (DCD) was introduced as the color feature detector; and the k-mean clustering operator was embedded at the time of color feature extraction to enhance the color area and extract the color feature accurately. Secondly, each trademark was quantified as the maximum of eight colors, to extract the spatial layout information of each color component. Then, a technique based on fuzzy histogram analysis was defined by means of different weights to balance the importance of color and space features. The adaptive coefficient of each trademark was calculated to accurately describe the image features of a color trademark. Finally, the Euclidean distance was used to measure the similarity and output the retrieved trademark. The experimental results showed that, the proposed algorithm had higher retrieval accuracy and robustness compared with the current trademark retrieval methods, and presented a more ideal P-R curve. Its retrieval accuracy could still reach 90% when the recall rate was 0.7. The proposed retrieval method has higher retrieval accuracy and good application values in the field of package trademark detection and trademark copyright protection, etc.