MATLAB Answers


How to eliminate erroneous match(es) in matchFeatures example?

Asked by Canberk Suat Gurel on 22 Mar 2018
Latest activity Commented on by Image Analyst
on 23 Mar 2018
Hi all,
I have a set of images that are taken from the dash cam of a car. I am trying to find a set of corresponding points in two successive frames to estimate the direction of the car. (I will use this information to obtain the visual odometry of the car). I used the match features code given here:
But sometimes I am getting wrong matches. For example:
My function:
function [matchedPoints1, matchedPoints2] = Corresponding_Points(Im1,Im2)
%%Find Corresponding Interest Points Between Pair of Images
% Find the corners.
points1 = detectHarrisFeatures(Im1);
points2 = detectHarrisFeatures(Im2);
% Extract the neighborhood features.
[features1,valid_points1] = extractFeatures(Im1,points1);
[features2,valid_points2] = extractFeatures(Im2,points2);
% Match the features.
indexPairs = matchFeatures(features1,features2);
% Retrieve the locations of the corresponding points for each image.
matchedPoints1 = valid_points1(indexPairs(:,1),:);
matchedPoints2 = valid_points2(indexPairs(:,2),:);
My code:
[matchedPoints1, matchedPoints2] = Corresponding_Points(image_1_gray,image_2_gray);
x1 = matchedPoints1.Location';
x2 = matchedPoints2.Location';
Note: the returned matchedPoints1 and matchedPoints2 belong to class cornerPoints . Using matchedPoints1.Location returns a matrix type single. (I am using Matlab 2016a.)


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1 Answer

Answer by Image Analyst
on 22 Mar 2018
 Accepted Answer

Do you know the (x,y) coordinates of each? You could just throw out any pairs where the distance between them is more than, say 10% of the image width.


Thank you for your answer. Yes, I know their (x,y) coordinates. I can do something like this:
for i = 1:length(x1)
d = sqrt((x1(1,i)-x2(1,i))^2+(x1(2,i)-x2(2,i))^2)
x1(:,i) = [];
x2(:,i) = [];
Can you think of a more efficient method? Getting rid of the for loop would be great.
Not sure if shrinking the array at every iteration is efficient. Maybe try just keeping track of columns to keep and vectorize it and extract:
distances = sqrt((x1(1,:)-x2(1,:)).^2+(x1(2,:)-x2(2,:)).^2)
columnsToKeep = distances < 100;
x1 = x1(:, columnsToKeep);
x2 = x2(:, columnsToKeep);

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