我正在开发图像识别应用程序,但是有些问题困扰着我。
我正在使用双色调图像(文档)。如果我复制同一图像文件并进行比较(实际上是比较两个[同一子区域]的子区域),则使用SURF不会获得100%的匹配。这是我的代码的一部分:
public double FindPercentMatch(Bitmap obj, Bitmap scene)
{
// get scene key points
VectorOfKeyPoint scenePoints = GetKeyPoints((Bitmap)scene.Clone());
// if no scene points found, no need to go any further
if (scenePoints == null || scenePoints.Size == 0) { return 0; }
// get object key points
VectorOfKeyPoint objectPoints = GetKeyPoints((Bitmap)obj.Clone());
// if not enough object key points found vs scene key points, then match can't be close enough (since
// you can't have more matches than scene points anyway, so don't even try to match
if (objectPoints == null || objectPoints.Size == 0 || (scenePoints.Size / objectPoints.Size < .15)) { return 0; }
// we have enough key points, so compute descriptors for scene and object
Matrix<float> objectDescriptors = GetDescriptors(objectPoints,(Bitmap)obj.Clone());
Matrix<float> sceneDescriptors = GetDescriptors(scenePoints, (Bitmap)scene.Clone());
int objectDescriptorCount = objectDescriptors == null ? 0 : objectDescriptors.Size.Height;
int sceneDescriptorCount = sceneDescriptors == null ? 0 : sceneDescriptors.Size.Height;
// find matches
int sim = FindMatches(objectDescriptors, sceneDescriptors);
// for testing so we know how many were found so we can monitor it
log.Debug("descriptors1 = " + objectDescriptorCount + ", 2 = " + sceneDescriptorCount + ", matches=" + sim);
double percent = 0;
if (sim != 0)
{
percent = objectDescriptorCount != 0 ? (double)sim / (double)objectDescriptorCount : 0;
log.Debug(percent * 100 + "%");
}
return percent;
}
public int FindMatches(Matrix<float> dbDescriptors, Matrix<float> queryDescriptors)
{
double uniquenessThreshold = 0.6;
if (dbDescriptors == null || queryDescriptors == null)
{
return 0;
}
var indices = new Matrix<int>(queryDescriptors.Rows, 2); // matrix that will contain indices of the 2-nearest neighbors found
var dists = new Matrix<float>(queryDescriptors.Rows, 2); // matrix that will contain distances to the 2-nearest neighbors found
// create FLANN index with 4 kd-trees and perform KNN search over it look for 2 nearest neighbours
var flannIndex = new Index(dbDescriptors, 4);
flannIndex.KnnSearch(queryDescriptors, indices, dists, 2, 24);
// for eatch match over a certain threshold, add +1 to the number of 'good' matches
int sim = 0;
for (int i = 0; i < indices.Rows; i++)
{
// filter out all inadequate pairs based on distance between pairs
if (dists.Data[i, 0] < (uniquenessThreshold * dists.Data[i, 1]))
{
sim++;
}
}
return sim;
}
在图像的同一子区域上使用FindPercentMatch时,预期结果将为100%,但根据图像的不同,可能为70%,99%,甚至看到了101%。
最佳答案
据我所知,您的过滤不会导致一对一的objectdescriptor-scenedescriptor(匹配某个阈值),这就是为什么您可以获得100%以上的百分比
另一件事是“objectDescriptorCount等于sceneDescriptorCount”这一事实并不总是意味着“objectDescriptor等于sceneDescriptor”。手动检查描述符,如果它们相同,则意味着处理逻辑有误(计数为“sim”)
希望能有所帮助
关于c# - 为什么精确的图像没有精确的描述符?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/32529451/