The invention provides a slant vehicle detection and tracking system and method based on machine vision. The system comprises a CCD camera, a USB data transmission port and a computer terminal. The method comprises the following steps of: in vehicle detection phase, firstly, image preprocessing is performed, region-of-interest extraction and improved lane line detection are combined, an inclined vehicle detection area is divided; an adaptive threshold value and a maximum between-class variance method are adopted; a shadow area is extracted, further a shadow line is extracted at the bottom of the vehicle, left and right boundaries of the vehicle are determined in combination with Sobel vertical edge extraction to obtain a suspected rectangular frame of a vehicle target, then features in the rectangular frame are extracted, dimensionality reduction is performed on the features by adopting kernel principal component analysis, and detection confirmation is performed by utilizing an Adaboost cascade classifier; in the vehicle tracking stage, mean shift and Kalman filtering are combined, a vehicle detection result is used as an initial tracking target, and the tracking target is screened by using rectangular frame coincidence. The system and the method can realize real-time vehicle detection and tracking, and have high accuracy.