The invention discloses a black smoke vehicle detection method based on a self-organizing background difference model and a multi-feature fusion, which comprises the following steps: detecting a moving object from a video surveillance by using the self-organizing background difference model, and determining a key area; transforming the key region image into YCrCb color space and extracting the color moment feature; transforming the key regions into gray space, and extracting the local ternary mode histogram and edge direction histogram; according to the position of the key region of the current frame, extracting the corresponding regions of several frames from the whole frame sequence, concatenating the same features extracted from all the temporal regions to form the feature vectors of each class, and normalizing the feature vectors of each class to form the final feature vectors; classifying the final eigenvectors by using the pruned radial basis function neural network classifier; identifying the key areas of smoke and further identifying the smoky vehicles. The invention can further improve the identification rate, reduce the false alarm rate, and has good identification effecton smoky vehicles with relatively light black smoke.