the different locations. $p_t$ and $p_f$ can be estimated by $$\label{eq:LRF19}
{p_t=\delta+(1-\delta)\zeta{m}/M},$$ and $$\label{eq:LRF20}
{p_f=\zeta(1-\delta)(m/M)},$$ where $\delta$ is the probability of a correspondence being correct, $m$ is the amount of keypoints in region $b$, $M$ is the size of $\mathcal{K}^{'}$ in $I^{'}$, and $\zeta$ is a factor added to balance deviations caused by repeated structures. A quantitative score is next designed to evaluate the distinction between two distributions as $$\label{eq:LRF21}
{{P}=\frac{{{m}_{t}}-{{m}_{f}}}{{{s}_{t}}+{{s}_{f}}}},$$ where $m$ is the mean value and $s$ is the standard deviation. This equation can be simplified as $$\label{eq:LRF22}
{{P}\propto \sqrt{Kn}},$$ where the distinction is positive correlated to the number of correspondences.

In addition, to incorporate this approach into a real-time system, a fast gird-based score estimator is developed as follows. First, $I$ and $I^{'}$ are divided into $20\times20$ non-overlapping cells. Second, for each cell in $I$, the cell containing the maximum amount of correspondences is grouped in $I^{'}$. Third, in cell-pair $(i,j)$ as well as its small neighborhoods (eight cell-pairs), $S_{ij}$ is estimated as $$\label{eq:LRF23}
{{{S}_{ij}}=\sum\limits_{k=1}^{K=9}{\left| {{\chi }_{{{i}^{k}}{{j}^{k}}}} \right|}},$$ where $\left|{\chi}\right|$ is the amount of correspondences in the cell-pair $(i^{k},j^{k})$. All correspondences in $(i,j)$ are judged as inliers if $S_{ij}>t_{gms}$, where $t_{gms}$ is a threshold approximated by $\alpha 