Conventional image detection techniques require scanning a picture in its entirety to detect a target image therein. However, the conventional image detection techniques necessitate a large number of scan windows and thus render the system busier to the detriment of its performance, not to mention that it is a waste of time detecting for non-target images. Referring to FIG. 1(A), a conventional image detection technique requires scanning a picture in its entirety to detect a target image therein and thus necessitates a large number of scan windows as shown in FIG. 1(B).
In an attempt to overcome the aforesaid drawback of the prior art, a speeded up robust features (SURF) algorithm was invented and involves retrieving characteristic points from a picture and then performing a block scan on the retrieved characteristic points to detect for a target image. SURF has an advantage: it speeds up image detection, because it does not require scanning the picture in its entirety. However, SURF has a drawback: the block scan performed on the retrieved characteristic points is disadvantaged by the presence of non-target image blocks. As a result, SURF still has room for improvement in terms of efficiency.