It is a conventional belief that line-based approaches perform better than point-based ones for homography estimation, as the linefitting is generally more noise resistant than point detection. In this note, we show that blithely using line-based estimation is a risky business. More specifically, we show that when the image line(s) is (are) passing through or close to the origin, the line-based homography estimation could become wildly unstable whereas the point-based estimation performs normally. To tackle this problem, a new normalized method specially designed for line-based homography estimation is proposed and validated by extensive experiments.