背景故事,在我的国家,每个银行面额都有一张其创始人父亲的照片:
我想通过冲浪探测器找到这两个图像之间的相似性。系统将由两个图像进行训练。用户将通过网络摄像头显示底部图片或顶部图片,并使用它们之间的相似性分数来查找其面额值。
My pseudocode:
1.Detect keypoints and the corresponding descriptors of both the images via surf detector and descriptor .
2.a.Calculate the matching vector between the query and each of the trained example .Find number of good matches / total number of matches for each image .
2.b.OR Apply RANSAC algorithm and find the highest number of closest pair between query and training algorithm
3.The one having the higher value will have higher score and better similarity.
我的方法听起来是否足够,或者是否有任何其他方法可以找到两个图像之间的相似性,其中查询图像将经历各种变换。我已经为此寻找解决方案,例如找到曼哈顿距离,或找到相关性,但是这些都不足以解决这个问题。
答案 0 :(得分:1)
是的,你这样做是正确的
1) You create a training set and store all its feature-points .
2) Perform ratio test for matches with the query and train feature-points.
3) Apply ransac test and draw matches (apply homograpghy if you want highlight the detected note).
This论文可能会有所帮助,他们使用SIFT做了类似的事情
答案 1 :(得分:0)
您的算法看起来很好,但您可以使用更多信息。我将为您提供一系列信息,您可以使用这些信息进一步改善结果:
1. Location of the part where denominations are written on the image.
2. Information about how denominations are written - Script knowledge.
3. Homo-graphic information as you know the original image and The observed image
利用以上所有信息改善结果。