@param depth width and height. higher values will create a stronger effect @return a kernel creating a horizontal emboss effect

<pre> 1 0 0 0 0 0 0 0 -1 </pre> @param depth width and height. higher values will create a stronger effect @return a kernel creating a l

<pre> 0 0 1 0 0 0 -1 0 0 </pre> @param depth width and height. higher values will create a stronger effect @return a kernel creating a right d

<pre> 0 0 0 1 0 -1 0 0 0 </pre> @param depth width and height. higher values will create a stronger effect @return a kernel creating a righ

The hamming distance of the same image has to be 0 @param bitRes the bit resolution of the algorithm

< The hamming distance of the same image has to be 0 @deprecated not really a algorithm test case. Same as consistent @param d1

The hamming distance of the same image has to be 0 @param bitRes the bit resolution of the algorithm @see https://github.com/KilianB/JImageHash/issue

The normalized hamming distance of the same image has to be 0 @param bitRes the bit resolution of the algorithm

May not add filter after id has been calculated

May not add filter after hashing operation

May not remove filter after id has been calculated

May not remove filter after hashing operation

Return an immutable map copy of the algorithms currently used in the matcher. This map is a hard copy of the hashmap and does not updated if the under

Return all images stored in the database which are considered matches to other images in the database. <p> Be careful that depending on the number of

Return the categories sorted by the number of images mapped to the category. An image is considered part of a category if it was either added by calli

@return the category

Get the certainty of a bit at the given bit position. <p> The returned value is in the range [-1,1]. A negative value indicates that the bit is more

Get the average hash representing the midpoint of the category cluster. @param algorithm the algorithm to get the hash for @param category the categ

Return all elements of the tree whose hamming distance is smaller or equal than the supplied max distance. If the tree is configured to ensureHashCon

Get the current false positive probability of the filter using the {@link #getApproximateDistinctElementsInFilter()} guess to assume the number of ele

Get a database image matcher which previously was serialized using {@link #serializeToDatabase(int)}. If the serialized matcher does not exist the con

Get the unique id's of all images mapped to this category @param category to check for @return a list of all unique id's mapped to this category