Evaluation of performance fruit detection algorithm and training the algorithm
1 次查看(过去 30 天)
显示 更早的评论
I am trying to find a way to evaluate the performance of my fruit detection algorithm. The detection of the fruit is currently done with the circular Hough transform. How can I compare this result with the original RGB image and therefore check if the detected fruit are a true positive or a false positive (to calculate the accuracy)? And how is it possible to train the algorithm?
I have added the original RGB image, the black-white image after preprocessing and the parameters of the CHT algorithm.
[centers,radii, metric] = imfindcircles(BW_Canny,[Rmin Rmax],'Sensitivity',0.95,'EdgeThreshold',0.15); % 0.95 0.15
% d = imdistline; %To check manually the approximate radius of the fruit in the image
viscircles(centers, radii,'EdgeColor','b');
For example for image 41, there are 3 true positives and 1 false positive.
回答(1 个)
yanqi liu
2022-1-11
in object detect application,may be use evaluateDetectionPrecision to compare detect location and real location,such as
0 个评论
另请参阅
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!