/// <summary>
/// Set search options from the UI (method, filter and similarity cutoff)
/// </summary>
private void ReadSearchOptions()
{
// method
switch (this.CBMethod.SelectedIndex)
{
case 0:
option_image_hash = Images.ImageHashAlgorithm.Average;
break;
case 1:
option_image_hash = Images.ImageHashAlgorithm.AverageHistogram;
break;
case 2:
option_image_hash = Images.ImageHashAlgorithm.AverageColor;
break;
case 3:
option_image_hash = Images.ImageHashAlgorithm.Block;
break;
case 4:
option_image_hash = Images.ImageHashAlgorithm.BlockHistogram;
break;
case 5:
option_image_hash = Images.ImageHashAlgorithm.BlockColor;
break;
case 6:
option_image_hash = Images.ImageHashAlgorithm.Color;
break;
case 7:
option_image_hash = Images.ImageHashAlgorithm.Difference;
break;
case 8:
option_image_hash = Images.ImageHashAlgorithm.DifferenceHistogram;
break;
case 9:
option_image_hash = Images.ImageHashAlgorithm.DifferenceColor;
break;
case 10:
option_image_hash = Images.ImageHashAlgorithm.Histogram;
break;
case 11:
option_image_hash = Images.ImageHashAlgorithm.Perceptive;
break;
case 12:
option_image_hash = Images.ImageHashAlgorithm.PerceptiveHistogram;
break;
case 13:
option_image_hash = Images.ImageHashAlgorithm.PerceptiveColor;
break;
default:
option_image_hash = Images.ImageHashAlgorithm.PerceptiveHistogram;
break;
}
// filter
switch (this.CBFilter.SelectedIndex)
{
case 0:
option_filter_colors = Images.ComparisonMethod.None;
break;
case 1:
option_filter_colors = Images.ComparisonMethod.MainColor;
break;
case 2:
option_filter_colors = Images.ComparisonMethod.TopColors;
break;
case 3:
option_filter_colors = Images.ComparisonMethod.PixelsDifference;
break;
case 4:
option_filter_colors = Images.ComparisonMethod.PixelsDifferenceSorted;
break;
case 5:
option_filter_colors = Images.ComparisonMethod.PixelsDistance;
break;
case 6:
option_filter_colors = Images.ComparisonMethod.PixelsDistanceSorted;
break;
default:
option_filter_colors = Images.ComparisonMethod.TopColors;
break;
}
// similarity
switch (this.CBSimilarity.SelectedIndex)
{
case 0:
option_similarity_cutoff = 65;
break;
case 1:
option_similarity_cutoff = 70;
break;
case 2:
option_similarity_cutoff = 75;
break;
case 3:
option_similarity_cutoff = 80;
break;
case 4:
option_similarity_cutoff = 85;
break;
case 5:
option_similarity_cutoff = 90;
break;
case 6:
option_similarity_cutoff = 95;
break;
case 7:
option_similarity_cutoff = 100;
break;
default:
option_similarity_cutoff = 90;
break;
}
}
/// <summary>
/// Search similar images
/// </summary>
/// <param name="image"> path of image of interest </param>
/// <param name="imagehash"> Image hash algorithm </param>
/// <param name="filter_method"> Color filtering method </param>
/// <param name="similarity_cutoff"> min. similarity % </param>
/// <returns></returns>
public Dictionary <string, int> SearchSimilarImages(string image, Images.ImageHashAlgorithm imagehash, Images.ComparisonMethod filter_method, int similarity_cutoff)
{
var matches = new Dictionary <string, int>();
similar_images_found = new Dictionary <string, int> [number_of_index];
Parallel.For(0, number_of_index, i =>
{
var found = new Dictionary <string, int>();
found.Add(image, 100);
if (index_list[i].Count > 0)
{
found = index_list[i].SearchSimilarImages(image, imagehash, filter_method, similarity_cutoff);
}
similar_images_found[i] = found;
});
if (similar_images_found == null)
{
return(matches);
}
if (similar_images_found.Length == 0)
{
return(matches);
}
foreach (var images_found in similar_images_found)
{
matches = matches.Union(images_found).ToDictionary(k => k.Key, v => v.Value);
}
return(matches);
}
