Package dev.brachtendorf.jimagehash.matcher.categorize

Class WeightedCategoricalMatcher

java.lang.Object

dev.brachtendorf.jimagehash.matcher.PlainImageMatcher

dev.brachtendorf.jimagehash.matcher.categorize.AbstractCategoricalMatcher

dev.brachtendorf.jimagehash.matcher.categorize.CategoricalMatcher

dev.brachtendorf.jimagehash.matcher.categorize.WeightedCategoricalMatcher

All Implemented Interfaces:

CategoricalImageMatcher

public class WeightedCategoricalMatcher
extends CategoricalMatcher

Cluster images into common categories. This matcher clusters images by computing the distance to the closest cluster and adds an image if it is within a given distance. This method works only approximate CategoricalMatcher.recomputeCategories() has to be called after images have been added.

Cluster centeroids are represented as FuzzyHashes a prot hash represented as mode hash of all added images.

Opposed to the categorical matcher this matcher calculates the distances to clusters using the weighted distance, resulting in more accurate results but at the cost of increase computational requirements.

Since:

3.0.0

Author:

Kilian

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	WeightedCategoricalMatcher.DimReduction

Field Summary

Fields

Modifier and Type	Field	Description
protected ClusterResult[]	clusterResult
protected FuzzyBinaryTree	fuzzyBinaryTree

Fields inherited from class dev.brachtendorf.jimagehash.matcher.categorize.CategoricalMatcher

cachedHashes, categories, categoriesAltered, clusterHash, clusterQuality, clusterRecomputed, clusterReverseLookup, newCategoryThreshold, subCategoryMatcher

Fields inherited from class dev.brachtendorf.jimagehash.matcher.categorize.AbstractCategoricalMatcher

cachedImagesInCategory, reverseImageCategoryMap

Fields inherited from class dev.brachtendorf.jimagehash.matcher.PlainImageMatcher

steps

Constructor Summary

Constructors

Constructor	Description
WeightedCategoricalMatcher(double newCategoryThreshold, WeightedCategoricalMatcher.DimReduction reductionTechnique)

Method Summary

Modifier and Type	Method	Description
boolean	addHashingAlgorithm(HashingAlgorithm algo)	Append a new hashing algorithm to be used by this matcher.
protected void	clusterPostcomputation()	Method invoked after CategoricalMatcher.recomputeClusters(int) is being called.
protected void	clusterPrecomputation()	Method invoked before CategoricalMatcher.recomputeClusters(int) is being called.
protected double	computeDistanceForCategory(Hash[] hashes, int category, double bestDistance)	Compute the distance between an image and a category cluster midpoint.
protected double	computeDistanceToCluster(FuzzyHash cluster, Hash imageHash)
protected int	getCategory(int iter, String uniqueId, Hash[] hashes, Set<Integer> categoriesAltered)

Methods inherited from class dev.brachtendorf.jimagehash.matcher.categorize.CategoricalMatcher

addCategoricalImage, addCategoricalImage, addCategoricalImage, addCategoricalImages, addCategoricalImages, categoricalHashToImage, categorizeImage, categorizeImage, categorizeImage, categorizeImageAndAdd, cleanupEmptyCategories, getAverageDistanceWithinCluster, getCategories, getCategoriesSortedByImageCount, getClusterAverageHash, printClusterInfo, recomputeCategories, recomputeClusters, resetBitWeights, updateCategories

Methods inherited from class dev.brachtendorf.jimagehash.matcher.categorize.AbstractCategoricalMatcher

getCategory, getImageCountInCategory, getImagesInCategory, isCategorized

Methods inherited from class dev.brachtendorf.jimagehash.matcher.PlainImageMatcher

clearHashingAlgorithms, equals, getAlgorithms, hashCode, removeHashingAlgorithm

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface dev.brachtendorf.jimagehash.matcher.categorize.CategoricalImageMatcher

categorizeImage, categorizeImageAndAdd

Field Detail

clusterResult

protected transient ClusterResult[] clusterResult

fuzzyBinaryTree

protected transient FuzzyBinaryTree fuzzyBinaryTree

Constructor Detail

WeightedCategoricalMatcher

public WeightedCategoricalMatcher(double newCategoryThreshold,
                                  WeightedCategoricalMatcher.DimReduction reductionTechnique)

Method Detail

clusterPostcomputation

protected void clusterPostcomputation()

Description copied from class: CategoricalMatcher

Method invoked after CategoricalMatcher.recomputeClusters(int) is being called.

Overrides:

clusterPostcomputation in class CategoricalMatcher

clusterPrecomputation

protected void clusterPrecomputation()

Description copied from class: CategoricalMatcher

Method invoked before CategoricalMatcher.recomputeClusters(int) is being called.

Overrides:

clusterPrecomputation in class CategoricalMatcher

getCategory

protected int getCategory(int iter,
                          String uniqueId,
                          Hash[] hashes,
                          Set<Integer> categoriesAltered)

Overrides:

getCategory in class CategoricalMatcher

computeDistanceForCategory

protected double computeDistanceForCategory(Hash[] hashes,
                                            int category,
                                            double bestDistance)

Description copied from class: CategoricalMatcher

Compute the distance between an image and a category cluster midpoint. This method is used to compute the minimum distance and therefore might cut the computation short if the distance is higher than the supplied best distance cutoff.

Overrides:

computeDistanceForCategory in class CategoricalMatcher

Parameters:

hashes - an array containing the hash for an image for each hashing algorithm added to this matcher

category - the category to compute the distance for

bestDistance - the best distance found so far. May be used to

Returns:

the distance between the image and the category midpoint or Double.MAX_VALUE if bestDistance was reached and copmutation was not finished

addHashingAlgorithm

public boolean addHashingAlgorithm(HashingAlgorithm algo)

Description copied from class: PlainImageMatcher

Append a new hashing algorithm to be used by this matcher. The same algorithm may only be added once. Attempts to add the same algorithm twice is a NOP.

For some matchers the order of added hashing algorithms is crucial. The order the hashes are added is preserved.

Overrides:

addHashingAlgorithm in class CategoricalMatcher

Parameters:

algo - The algorithms to be added

Returns:

true if the algorithm was added, false if it was already present

computeDistanceToCluster

protected double computeDistanceToCluster(FuzzyHash cluster,
                                          Hash imageHash)

Overrides:

computeDistanceToCluster in class CategoricalMatcher