Benchmarks

FVC-onGoing provides various benchmarks to evaluate and compare recognition algorithms. Each benchmark is based on a sequestered dataset that will not evolve over time; in case new datasets will be added in the future, they will form a different benchmark (or a new version of an existing one). Only results obtained on the same data will be compared.

Benchmarks are grouped into Benchmark Areas according to the (sub)problem addressed and the evaluation protocol adopted. In the following, the currently available benchmark areas and the corresponding benchmarks are briefly described.

	Fingerprint Verification	Benchmarks	Leaded by
	This benchmark area contains fingerprint verification benchmarks. Fingerprint verification consists in comparing two fingerprints to determine whether they are impressions of the same finger or not (one-to-one comparisons). Algorithms submitted to these benchmarks are required to enroll fingerprints into proprietary or standard templates and to compare such templates to produce a similarity score. Read more...	FV-STD-1.0 FV-TEST FV-HARD-1.0
	Palmprint Verification	Benchmarks	Leaded by
	This benchmark area contains palmprint verification benchmarks. Palmprint verification consists in comparing two palmprints to determine whether they are impressions of the same palm or not (one-to-one comparisons). Algorithms submitted to these benchmarks are required to enroll palmprints into proprietary or standard templates and to compare such templates to produce a similarity score. Read more...	PV-TEST-FULL PV-TEST-PARTIAL PV-FULL-1.0 PV-PARTIAL-1.0
	Fingerprint Matching (ISO)	Benchmarks	Leaded by
	This benchmark area contains fingerprint matching benchmarks using a standard minutiae-based template format [ISO/IEC 19794-2 (2005)]. Algorithms submitted to these benchmarks are required to compare ISO fingerprint templates to determine whether they are impressions of the same finger or not (one-to-one comparisons). No fingerprint enrollment (feature extraction) is required, only the minutiae matching algorithms are evaluated by these benchmarks. Read more...	FMISO-STD-1.0 FMISO-TEST FMISO-HARD-1.0
	Fingerprint Indexing	Benchmarks	Leaded by
	This benchmark area contains fingerprint indexing benchmarks. Fingerprint indexing consists in comparing a query fingerprint against a large database and to select the most similar candidates. Algorithms submitted to these benchmarks are required to search a set of query fingerprints over a given fingerprint database, producing, for each query, a candidate list containing the most similar database fingerprints sorted by similarity. Read more...	FIDX-TEST FIDX-10K-1.0 FIDX-50K-1.0
	Fingerprint Orientation Extraction	Benchmarks	Leaded by
	The estimation of local fingerprint orientations is a fundamental step in fingerprint analysis and recognition (e.g., it is a prerequisite for image enhancement). This benchmark area contains benchmarks for local orientation extraction algorithms. Algorithms submitted to these benchmarks are required to extract local orientations from fingerprint images and to save them into a specific format. The extracted orientations are compared to the ground-truth in order to assess the algorithm accuracy. Read more...	FOE-TEST FOE-STD-1.0
	Secure Template Fingerprint Verification	Benchmarks	Leaded by
	This benchmark area contains fingerprint verification benchmarks for algorithms relying on protected templates to enhance privacy. Algorithms submitted to these benchmarks are required to enroll a given fingerprint into a protected template (that is, a template from which the fingerprint features cannot be extracted) and to compare it against a given fingerprint image. Read more...	STFV-TEST STFV-STD-1.0 STFV-HARD-1.0
	Face Image ISO Compliance Verification	Benchmarks	Leaded by
	This benchmark area contains face image ISO compliance verification benchmarks. Algorithms submitted to these benchmarks are required to check the compliance of face images to ISO standard. Read more...	FICV-TEST FICV-1.0
	Single-image Morph Attack Detection	Benchmarks	Leaded by
	This benchmark area contains face morphing detection benchmarks. Morphing detection consists in analyzing a face image to determine whether it is the result of a morphing process (mixing faces of two subjects) or not. Algorithms submitted to these benchmarks are required to analyze a suspected morph image and produce a score representing the probability of the image to be morphed. Read more...	SMAD-TEST SMAD-BIOLAB-1.0 SMAD-MORPHDB_D-1.0 SMAD-MORPHDB_P&S-1.0 SMAD-SOTAMD_D-1.0 SMAD-SOTAMD_P&S-1.0 SMAD-SOTAMD_PM_D-1.0 SMAD-SOTAMD_UC_P&S-1.0 SMAD-IMARS-HQ_FULL-1.0 SMAD-IMARS-MQ_FULL-1.0 SMAD-IMARS-HQ_SMALL-1.0 SMAD-IMARS-HQ_HARD-1.0 SMAD-IMARS-MQ_SMALL-1.0 SMAD-IMARS-MQ_HARD-1.0
	Differential Morph Attack Detection	Benchmarks	Leaded by
	This benchmark area contains face morphing detection benchmarks. Morphing detection consists in analyzing a face image to determine whether it is the result of a morphing process (mixing faces of two subjects) or not. Algorithms submitted to these benchmarks are required to compare a suspected morph image to a bona fide (not morphed) one and produce a score representing the probability of the suspected morph image to be a morphed face image. Read more...	DMAD-TEST DMAD-MORPHDB_D-1.0 DMAD-MORPHDB_P&S-1.0 DMAD-BIOLAB-1.0 DMAD-SOTAMD_D-1.0 DMAD-SOTAMD_P&S-1.0 DMAD-SOTAMD_PM_D-1.0 DMAD-SOTAMD_UC_P&S-1.0 DMAD-IMARS-HQ_FULL-1.0 DMAD-IMARS-MQ_FULL-1.0 DMAD-IMARS-HQ_SMALL-1.0 DMAD-IMARS-HQ_HARD-1.0 DMAD-IMARS-MQ_SMALL-1.0 DMAD-IMARS-MQ_HARD-1.0