Version	1	/	Date	of	Issue:	10.29.15	/	Issuing	Authority:	Forensic	Science	Standards	Board	(FSSB)

OSAC	Research	Needs Assessment Form

Title	of	research	need:

Keywords:

Submitting subcommittee(s): Date	Approved:

(If	SAC	review	identifies	additional	subcommittees,	add	them	to	the	box	above.)

Background	information:

1.	 Description	of	research	need:

2.	 Key	bibliographic	references	relating	to	this research	need:

(1)	Research	on	the	effectiveness	and	reliability	of	using	automated LFIQ	(latent	finger	image	

quality)	scores	to	systematically	determine	suitability and	assign	verification	levels,	e.g.	oneperson,	two-person,	blind,	non-blind,	etc.	(2)	Develop	tools	regarding	the	calculation	of	manually	

derived	latent	image	quality	scores	based	on	the	image	quality	map	described	in	"Markup	

Instructions	for	Extended	Friction	Ridge	Features"	(NIST	Special	Publication	1151).		(3)	Research	

whether	examiner	derived	scores	could	then	be	compared	to	automated	LFIQ	to	determine	if	these	

mark-ups	have	greater	predictive	power	than	automated LFIQ	scores	alone,	or	if	those	two	

techniques	can	be	combined	to	add	to	that	predictive	power.		(4)		Research	on	the	effectiveness	and	

reliability	of using	LFIQ	scoring	to	guide	Latent	Finger	Image	Search	(LFIS) vs.	Latent	Finger	

Feature Search (LFFS) AFIS	(Automated	Fingerprint	Identification	System)	searches.		(5)	Research	

on	the	effectiveness	and	reliability	of	using	AFIS	match	score	thresholding	to	reduce	latent	print	

AFIS	verification/comparison	workloads,	and	when	to	use	that	technology.

Latent Fingerprint	Image	Quality Usage

Image	Quality,	LFIQ,	AFIS,	Sufficiency,	Suitability

Friction	Ridge

Please	see	Appendix	“A”	for	a	normative	bibliography	related	to	this	research	topic.

For	a	comprehensive	and	informative	bibliography	related	to	friction	ridge	examination	please	see	

Appendix	“B”:			The	2011	SWGFAST	response	to	the	Research,	Development,	Testing	&	Evaluation	

Inter-Agency	Working	Group	of	the	National	Science	and	Technology	Council,	Committee	on	

Science,	Subcommittee	on	Forensic	Science.		
Version	1	/	Date	of	Issue:	10.29.15	/	Issuing	Authority:	Forensic	Science	Standards	Board	(FSSB)

3a.		In	what	ways	would	the	research	results	improve	current	laboratory	capabilities?

3b.		In	what	ways	would	the	research	results	improve	understanding	of	the	scientific	basis	for	the	

subcommittee(s)?

3c.		In	what	ways	would	the	research	results	improve	services	to	the	criminal	justice	system?

4.		Status assessment	(I,	II,	III,	or	IV):		 Major gap	

in	current	

knowledge

Minor gap	

in	current	

knowledge

No	or	limited

current	research	

is	being	

conducted

I III

Existing current	

research	is	being	

conducted

II IV

Latent	fingerprint	image	quality	measurements	have	proven	to	be	inconsistent.		Improvement	in	

this	technology	is necessary	to	reduce	error	and	improve	efficiency.		Improved	image	quality	

measurement	will	assist	examiners	in	the	ACE-V	(Analysis,	Comparison,	Evaluation	,	Verification)	

process	by	assessing	risk	of	error.	 Improved	LFIQ	measurement	will	also	help	streamline	

examination	and	AFIS	search	workflows	through systematically	determining	sufficiency,	as	well	as	

suitability	for	AFIS, and	level	of	verification	required.		This	type	of	tool	will	also	assist	researchers	

in	developing	and	validating	chemical	friction	ridge	detection	techniques.

It	is	difficult	to	standardize	AFIS	and	ACE-V	methodologies without	reliable	image	quality	

measurement	techniques.

Improved	image	quality	measurements	(providing	new	tools)	and	understanding	how	to	use	those	

metrics	will	likely	reduce	examiner	error	rates,	as	well	as	boost	workload	efficiency	by	assigning	

examiner	resources	through	rational	business	processes.

II
Version	1	/	Date	of	Issue:	10.29.15	/	Issuing	Authority:	Forensic	Science	Standards	Board	(FSSB)

This	research	need	has	been	identified	by	one	or	more	subcommittees	of	OSAC	and	is	being	provided	as	an	

informational	resource	to	the	community.

// Approval	date:

(Approval	is	by	majority	vote	of	subcommittee.		Once	approved,	forward	to SAC.)

1.		Does	the	SAC	agree	with	the	research	need?				Yes ⃝		

2.		Does	the	SAC	agree	with	the	status assessment?				Yes

If	no,	what	is	the	status assessment	of	the	SAC:

Approval	date:

(Approval	is	by	majority	vote	of	SAC.		Once	approved,	forward	to	NIST	for	posting.)

Subcommittee 01/29/2016

SA

C

17-Mar-2016
Version	1	/	Date	of	Issue:	10.29.15	/	Issuing	Authority:	Forensic	Science	Standards	Board	(FSSB)

APPENDIX	“A”

Alonso-Fernandez,		F.,		Fierrez,		J.,		Ortega-Garcia,		J.,		GonzalezRodriguez,	J.,	Fronthaler,	H.,	Kollreider,	K.,	

and	Bigun,	J.,	"A	Comparative		Study		of		Fingerprint		Image-Quality		Estimation	

Methods",		Information		Forensics		and		Security,		IEEE	Transactions	on,	vol.	2	(4),	pp.	734-743,	2007.

Blomeke,		C.		R.,		Modi,		S.		K.,		and		Elliott,		S.		J.,		"Investigating		the	Relationship		between		Fingerprint		

Image		Quality		and		Skin	Characteristics",		in		42nd		Annual		IEEE		International	

Carnahan		Conference		on		Security		Technology,		Prague,	Czech	Republic,	2008,	pp.	158-161.

Changlong,		J.,		Hakil,		K.,		Xuenan,		C.,		Eunsoo,		P.,		Junchul,		K.,	Jinsoo,		H.,		and		Elliott,		S.,		"Comparative		

Assessment		of	Fingerprint		Sample		Quality		Measures		Based		on		Minutiae Based	Matching	

Performance",	in		Electronic	Commerce	and	Security,	2009.	ISECS	'09.	Second	International	Symposium	

on,	2009,	pp.	309-313

Hicklin,	R.	Austin,	JoAnn	Buscaglia,	and	Maria	Antonia	Roberts.	"Assessing	the	Clarity	of	Friction	Ridge	

Impressions."	Forensic	Science	International	226	(2013):	106-17.

Indovina,	M.,	V.	Dvornychenko,	E.	Tabassi,	G.	Quinn,	P.	Grother,	S.	Meagher,	and	M.	Garris.	"Elft	Phase	II	-

an	Evaluation	of	Automated	Latent	Fingerprint	Identification	Technologies."	Washington	DC:	National	

Institute	of	Standard	and	Technology,	2009.

Indovina,	M.,	R.	A.	Hicklin,	and	G.	I.	Kiebuzinski.	"ELFT-EFS	Evaluation	of	Latent	Fingerprint	Technologies:	

Extended	Feature	[Sets	Evaluation	#1]."	Washington	DC:	U.S.	Department	of	Commerce,	National	

Institute	of	Standards	and	Technology,	2011.

Indovina,	M.,	V.	Dvornychenko,	R.	A.	Hicklin,	and	George	I.	Kiebuzinski.	"ELFT-EFS	Evaluation	of	Latent	

Fingerprint	Technologies:	Extended	Feature	Sets	[Evaluation	#2]."	National	Institute	of	Standards	and	

Technology,	U.S.	Department	of	Commerce,	2012.

Li,	Z.,	Han,	Z.,	and	Fu,	B.,	"A	Novel	Method	for	the	Fingerprint	Image	Quality		Evaluation",		in		

Computational		Intelligence		and	Software		Engineering,		2009.		CiSE		2009.		International	

Conference	on,	2009,	pp.	1-4.

Yoon,	Soweon,	Eryun	Liu,	and	Anil	K.	Jain.	"On	Latent	Fingerprint	Image	Quality."	In	Proceedings	of	the	

5th	International	Workshop	on	Computational	Forensics.	Tsukuba,	Japan,	2012.