All Classes

Class	Description
AbstractBinaryTree<T>
AbstractCategoricalMatcher	An abstract implementation of the categorical image matcher supporting classes to keep track of the categories an image was matched to.
AverageColorHash	Calculate a hash value based on the average rgb color in an image.
AverageHash	Calculate a hash value based on the average luminosity in an image.
AverageKernelHash	Calculate a hash value based on the average luminosity in an image.
BinaryTree<T>	A not thread safe binary tree implementation used to quickly compute the hamming distance of multiple hashes.
BloomFilter	A bloom filter is an approximative data structure with constant space and time guarantee to check if an image is likely in the set or definitely not present.
CategoricalImageMatcher	Image matcher allowing to group images into similar categories.
CategoricalMatcher	Cluster images into common categories.
CategorizationResult	A categorization result describes the membership to a cluster.
ClusterResult
ConsecutiveMatcher	Convenience class allowing to chain multiple hashing algorithms to find similar images.
ConsecutiveMatcher	Convenience class allowing to chain multiple hashing algorithms to find similar images.
CumulativeMatcher	Convenience class allowing to chain multiple hashing algorithms to find similar images.
CumulativeMatcher	Instead of early aborting if one algorithm fails like the ConsecutiveMatcher, this class looks at the summed distance and decides if images match.
DatabaseImageMatcher	A naive database based image matcher implementation.
DifferenceHash	Calculates a hash based on gradient tracking.
DifferenceHash.DHash	An extended hash class allowing dhashes to be visually represented.
DifferenceHash.Precision	Algorithm precision used during calculation.
Experimental
Filter	A filter modifies the content of an image while leaving the source image intact.
FuzzyBinaryTree	A binary tree implementation allowing to quickly lookup be aware that fuzzy trees currently are of one time use and are rendered invalid as soon as one of the underlying hashes changes it's internal state.! TODO for mutability add a list of uncertainties to each node and allow remove operation by supplying the old and the new fuzzy hash state
FuzzyHash	A fuzzy hash is an aggregation of multiple hashes mapped to a single mean hash representing the average hash while keeping track of fractional (probability) bits.
FuzzyNode	A tree node saving references to it's children.
H2DatabaseImageMatcher	A naive database based image matcher implementation.
Hash	Hashes are bit encoded encoded values (0101011101) created from images using a hashing algorithm.
HashBuilder	Helper class to quickly create a bitwise byte array representation which can be converted to a big integer object.
HashingAlgorithm	Base class for hashing algorithms returning perceptual hashes for supplied images reducing the number of bits needed to represent said image.
HashUtil
HogHash	Deprecated. not ready to use yet
HogHashAngularEncoded	Deprecated. not ready to use yet
HogHashDual	Deprecated. not ready to use yet
Kernel	Kernel operations are shifting window masks applied to data point of an array to recompute it's value.
Kernel.EdgeHandlingStrategy	The edge handling strategy defines the behaviour when a kernel reaches the edge of an image and does not have enough information to compute it's value.
Kernel.GrayScaleFilter	Kernels whose filter class work with grayscale instead of seperate color channels
KMeans
KMeansClassifier	The kMeans approach requires to know the number of clusters beforehand.
KMeansPlusPlus	Kmeans plus plus implementation.
LabeledImage	A labeled image used to benchmark hashing algorithms.
Leaf<T>	A leaf node in the binary tree containing multiple values associated with a specific hash value
MaximumKernel	A maximum kernel is a non linear filter scanning the image and replacing every value with the maximum value found in the neighborhood.
MedianHash	Calculate a hash value based on the median luminosity in an image.
MedianKernel	A median kernel is a non linear filter scanning the image and replacing every value with the median value found in the neighborhood.
MinimumKernel	A maximum kernel is a non linear filter scanning the image and replacing every value with the minimum value found in the neighborhood.
MultiKernel	Wrapper class to apply multiple kernels in a consecutive manner.
Node	A tree node saving references to it's children.
NodeInfo<T>	Helper class to iteratively search the tree {
NonAveragingKernel
OptimizationCriteria
PerceptiveHash	Calculate a hash based on the frequency of an image using the DCT T2.
PersistentImageMatcher	Persistent image matchers are a subset of TypedImageMatcher which can be saved to disk to be later reconstructed.
PersitentBinaryTreeMatcher	* Persistent image matchers are a subset of TypedImageMatcher which can be saved to disk to be later reconstructed.
PlainImageMatcher	Image matchers are a collection of classes bundling the hashing operation of one or multiple HashingAlgorithms together and usually exposing functionalities to compare multiple images with each other.
RandomForestCategorizer	Deprecated. not ready yet.
Result<T>	Search result returned when querying the tree
RotAverageHash	Calculate a hash value based on the average luminosity in an image after mapping each pixel to a rotational bucket.
RotPHash	A rotational invariant hashing algorithm which is mostly immune to rotation attacks.
ScharrFilter	Edge detection filter similar to the sobel operator.
SingleImageMatcher	Convenience class to chain multiple hashing algorithms to check if two images are similar.
SobelFilter	Edge detection filter
TypedImageMatcher	Image matchers are a collection of classes which bundle the hashing operation of one or multiple HashingAlgorithms and expose functionalities to compare multiple images with each other.
TypedImageMatcher.AlgoSettings	Settings used while computing if an algorithms consideres two images to be a close match
WaveletHash	Calculate a hash based on iterative application of a haar wavelet on the luminosity values of the input image.
WeightedCategoricalMatcher	Cluster images into common categories.
WeightedCategoricalMatcher.DimReduction