/// <summary>
/// Matches the provided template pyramid against the linearized memory maps pyramid.
/// </summary>
/// <param name="linPyr">Linearized memory pyramid.</param>
/// <param name="templPyr">Template pyramid.</param>
/// <param name="minMatchingPercentage">Minimum matching percentage [0..100].</param>
/// <returns>List of found matches.</returns>
public static List <Match> MatchTemplate(this LinearizedMapPyramid linPyr, ITemplatePyramid templPyr, int minMatchingPercentage = 85)
{
if (linPyr.PyramidalMaps.Length != templPyr.Templates.Length)
{
throw new Exception("Number of pyramids in linear pyramid must match the number of templates in template pyramid!" + "\n" +
"Check if the number of neighborhood per level is the same as the number of features per level for template!");
}
List <Match>[] pyrMatches = new List <Match> [linPyr.PyramidalMaps.Length];
//match at the lowest level
int lowestLevelIdx = linPyr.PyramidalMaps.Length - 1;
var searchArea = new Rectangle(new Point(), linPyr.PyramidalMaps[lowestLevelIdx].ImageSize); //search whole image
pyrMatches[lowestLevelIdx] = matchTemplate(linPyr.PyramidalMaps[lowestLevelIdx], templPyr.Templates[lowestLevelIdx], searchArea, minMatchingPercentage, true);
//refine matches
for (int pyrLevel = (lowestLevelIdx - 1); pyrLevel >= 0; pyrLevel--)
{
LinearizedMaps maps = linPyr.PyramidalMaps[pyrLevel];
ITemplate template = templPyr.Templates[pyrLevel];
Size imageValidSize = maps.ImageValidSize;
pyrMatches[pyrLevel] = new List <Match>();
int previousNeigborhood = linPyr.PyramidalMaps[pyrLevel + 1].NeigborhoodSize;
for (int candidateIdx = 0; candidateIdx < pyrMatches[pyrLevel + 1].Count; candidateIdx++) //for every candidate of previous pyramid level...
{
//translate match to lower pyrmaid level
Match canidate = pyrMatches[pyrLevel + 1][candidateIdx];
canidate.X = canidate.X * 2 + 1;
canidate.Y = canidate.Y * 2 + 1;
canidate.Template = template;
//translate search area to lower pyramid level
searchArea = new Rectangle //in originalImageSize coordinate system
{
X = System.Math.Max(0, canidate.X - previousNeigborhood),
Y = System.Math.Max(0, canidate.Y - previousNeigborhood),
Width = previousNeigborhood * 2,
Height = previousNeigborhood * 2
};
searchArea = searchArea.Intersect(imageValidSize);
var foundCandidates = matchTemplate(linPyr.PyramidalMaps[pyrLevel], template, searchArea, minMatchingPercentage, pyrLevel != 0 /*filter partial object for all levels except for the original one*/);
pyrMatches[pyrLevel].AddRange(foundCandidates);
}
}
return(pyrMatches[0]); //matches of the highest pyr level
}
/// <summary>
/// Matches the provided template pyramid against the linearized memory maps pyramid.
/// </summary>
/// <param name="linPyr">Linearized memory pyramid.</param>
/// <param name="templPyr">Template pyramid.</param>
/// <param name="minMatchingPercentage">Minimum matching percentage [0..100].</param>
/// <returns>List of found matches.</returns>
public static List<Match> MatchTemplate(this LinearizedMapPyramid linPyr, ITemplatePyramid templPyr, int minMatchingPercentage = 85)
{
if (linPyr.PyramidalMaps.Length != templPyr.Templates.Length)
throw new Exception("Number of pyramids in linear pyramid must match the number of templates in template pyramid!" + "\n" +
"Check if the number of neighborhood per level is the same as the number of features per level for template!");
List<Match>[] pyrMatches = new List<Match>[linPyr.PyramidalMaps.Length];
//match at the lowest level
int lowestLevelIdx = linPyr.PyramidalMaps.Length - 1;
var searchArea = new Rectangle(new Point(), linPyr.PyramidalMaps[lowestLevelIdx].ImageSize); //search whole image
pyrMatches[lowestLevelIdx] = matchTemplate(linPyr.PyramidalMaps[lowestLevelIdx], templPyr.Templates[lowestLevelIdx], searchArea, minMatchingPercentage, true);
//refine matches
for (int pyrLevel = (lowestLevelIdx - 1); pyrLevel >= 0; pyrLevel--)
{
LinearizedMaps maps = linPyr.PyramidalMaps[pyrLevel];
ITemplate template = templPyr.Templates[pyrLevel];
Size imageValidSize = maps.ImageValidSize;
pyrMatches[pyrLevel] = new List<Match>();
int previousNeigborhood = linPyr.PyramidalMaps[pyrLevel + 1].NeigborhoodSize;
for (int candidateIdx = 0; candidateIdx < pyrMatches[pyrLevel+1].Count; candidateIdx++) //for every candidate of previous pyramid level...
{
//translate match to lower pyrmaid level
Match canidate = pyrMatches[pyrLevel + 1][candidateIdx];
canidate.X = canidate.X * 2 + 1;
canidate.Y = canidate.Y * 2 + 1;
canidate.Template = template;
//translate search area to lower pyramid level
searchArea = new Rectangle //in originalImageSize coordinate system
{
X = System.Math.Max(0, canidate.X - previousNeigborhood),
Y = System.Math.Max(0, canidate.Y - previousNeigborhood),
Width = previousNeigborhood * 2,
Height = previousNeigborhood * 2
};
searchArea = searchArea.Intersect(imageValidSize);
var foundCandidates = matchTemplate(linPyr.PyramidalMaps[pyrLevel], template, searchArea, minMatchingPercentage, pyrLevel != 0 /*filter partial object for all levels except for the original one*/);
pyrMatches[pyrLevel].AddRange(foundCandidates);
}
}
return pyrMatches[0]; //matches of the highest pyr level
}
