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What you did until now is to match one set of keypoints with another set of keypoints (see my previous answer).

It means that for one keypoints, it will find the closest keypoint in the other image in term of descriptor distance, no matter if the two considered image are completly different.

To eliminate the false matches, you have to use a filtering strategie:

• keep only pair of keypoints whose the descriptor distance is below a specific threshold,
• keep only pair of keypoints whose the ratio between the two best matches are below a specific threshold,
• etc.

An example of the result after a filtering:

Finally, take a look at this tutorial, it is for Python but it is the concept which is important.