A target detection method based on improved Gabor filtering and regional growth is proposed for the influence of the relative motion of the background, the similarity of the object and the change of the external light. First it will do subtraction between two adjacent frames of the input video image, and then the L component of the Lab model in the difference image is subjected to Gabor filter processing,then we need to choose the right parameters according to different scenarios to extract the salient region of the target. In order to consider the operating speed and the significant features of the target,we need to select a pixel with a gray value as the seed point,and for the purpose of obtaining a more accurate target,we need to perform a region growing operation at a point within a certain range of gray value difference.Next,we need use corrosion and swelling to remove interference. Finally,to achieve the purpose of testing, the eight directions of filtering should be merged together, and the circumscribed rectangle is used to mark the target area that meets the requirements. Through parameter adjustment and experimental verification, the target detection rate of this method is improved to 90.89% compared with the low accuracy of the traditional detection algorithm, and it can have good robustness under the interference of external factors such as illumination and background.