The invention provides a front side
gait cycle detecting method based on video, which comprises the target profile capture of a
pedestrian and the
cycle detection of a front side
gait. Firstly, a single-frame image is extracted from the video, and is treated by
gray level transformation, and then an image without a
human body is used as the original
background image of the whole video; secondly, a
human body target is extracted by adopting a background deduction method with a real-time updated background, and binarization treatment is carried out on an
image sequence by a Kapur entropy threshold method; thirdly, the vacancy of the binarized image is filled up by
mathematical morphology, a human silhouette is extracted and analyzed by single communication so as to centralize the
human body, and all the sizes of the images are 64*64 pixels; finally, the extracted human body is detected, the redundant frames containing an incomplete human body are eliminated, and the number change of the pixels of a lower arm swinging area is used as the basis for judging the front side
gait cycle according to the relation of the proportion of the limbs to a
body height. The invention has significant effect on the detection of the front side
gait cycle, and the amount of calculation is small, thereby saving a large amount of storage space so as to make real-time gait identification possible.