Size/position identification in real-time image processing using run length encoding

This paper presents the use of run length encoding (RLE) for real-time image processing. RLE compresses the image and allows the processing algorithm to efficiently identify the size and position of the objects in the image. The algorithm is application to a robotic vision system enable to reliably identify 11 objects in the 16.67 ms sample time of an interlaced NTSC video image. It is shown that the time complexity of the compression phase is linear in the size of the image while the image processing phase is linear in the number of object in the image and the number of lines occupied by the objects in the image.