finding the best match between set of images using SIFT algorithm

33 次查看（过去 30 天）
KT
KT 2012-4-20
评论： khalil yossefi 2020-1-6
i am implementing SIFT algorithm , where my purpose of using this is that i have a set of images and i want to find the best match against a single image which i have kept it as 'template image' , SIFT gives us matches and scores in return , where 'matches' represent the descriptors that were found to be same in both image, and 'scores' determined by euclidean method, now i am stuck at the point that how can i evaluate the best match amongst all the images with my template image, i figured out that when there is a exact match between two images the 'score' turns out to be zero , because descriptors position in both the images are same,so can anyone guide me through that how shall i go about it that i can say this image is the best match or the second best match against template but using 'scores'.
  1 个评论
Laraib Kanwal
Laraib Kanwal 2015-10-1
Comparing one image (query image) against database of millions of image, its the same thing you are doing? "visual search"

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Junaid
Junaid 2012-4-23
As I understood, you want to do image to image matching. Let say your template image is T, and you set of images D. Each image (including your template image) will have many SIFT descriptors (vectors of 128-D).
I suggest you to use VLFEAT for image matching. Though you have your own SIFT implementation but still for matching your can use VLFEAT library. There is function VL_UBCMATCH which is used for SIFT matching. For all set of SIFT vectors in T you will find matching with all the images in D. And That image has maximum number of matches is considered to be similar image.
Though there are many other techniques because in image to image matching there can be two entirely different images can be matched to gather, therefore, there are many other techniques to reject the out-liers.
  4 个评论
显示 2更早的评论

请先登录，再进行评论。

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 SIFT - Scale Invariant Feature Transform 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by