To recognize and detect a rectangle rapidly and accurately, an image collection system was established and a rapid detection algorithm for rectangles was proposed based on Harris corner detection algorithm. First, the L-shaped corner points were selectively recognized from all kinds of corner points in the detecting image by improving the traditional Harris corner detection algorithm, and the position accuracy of corner points was promoted by sub-pixel post-processing. Then, according to the obtained high-precision angular position information, some parallel straight line segment pairs with equal length were grouped and the perpendicular parallel line segment pairs with four overlap corner points were matched, by which the four sides of a rectangle were obtained. Furthermore, all the rectangle elements were detected in the processed image. In order to improve the accuracy and reliability of the rectangular recognition algorithm, the identifying criterion of the pseudo rectangular graphic elements was provided. Finally, the sensor performance testing experiments were carried out. Experimental results indicate that the rectangular recognition speed of Harris corner point algorithm is 8.5 times faster than that of Hough algorithm, and the rectangular image recognition maximum position error is 0.4 pixel. The Harris corner rectangle detection method has strong anti-interference capability and stability and can meet the high real-time and precision detection requirements of industrial application.