Abstract: In image corner detection, classical approaches can not meet the demand of high accuracy but low computational complexity. A new line search algorithm for image corner detection is proposed in this paper. The new method employs a circle mask centered at the pixel in question, called the ``nucleus'' of the mask, to search all the straight lines that pass through the nucleus within the mask. Then, a corner point of an image is defined as the point (nucleus) where, among those straight lines, there is at least one straight line that does not cross the remaining part of the univalue segment assimilating nucleus (USAN) except a given neighborhood of the nucleus. This paper asserts the practicability and necessity of using finite search lines. To reduce the computational complexity, it employs dynamic search lines, finite points on each search line, and the coarse-to-fine search strategy as well. A new non-maximum suppression for accurate localization is proposed, and some new false response suppression measures are incorporated for good detection. Experiments show good performance of the new algorithm in both accuracy and speed.