The author(s) shown below used Federal funds provided by the U.S.

Department of Justice and prepared the following final report:

Document Title: Algorithmic Image Matching (AIM): Project

Analysis for Santa Ana Police Department

Author(s): Santa Ana Police Department

Document No.: 181955

Date Received: April 19, 2000

Award Number: 97-IJ-CX-K011

This report has not been published by the U.S. Department of Justice.

To provide better customer service, NCJRS has made this Federallyfunded grant final report available electronically in addition to

traditional paper copies.

Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect

the official position or policies of the U.S.

Department of Justice.
/Q/?55- 

Algorithmic Image Matching 

Technology Research And Development Partnership 

Projects For Community Policing 

Submitted to: National Institute of Justice 

Submitted by: Santa Ana Police Department 

In Partnership with: Pacer Infotec, Inc. 

U.S. Department of Justice.

of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
Algorithmic Image Matching (AIM) 

Project Analysis For 

Santa Ana Police Department 

M # 97-IJ-cXXOll 

(Replaces Id #: 97-IJCX-0019) 

February 10,1999 

1 .O Executive Summary 

Many organtzations throughout th: United States have adopted an electronic mug imaging 

system. These systems have prov& to be a reliable source for stonng and retrieving biographical 

and image information. Most have restrictions on the physical descriptions and types of searches 

available. 

Pacer Infotec Inc. partnered with the Santa Ana Police Depment to develop, integrate, 

implement, test, and evaluate a mug identification imagmg system that exceeds the current 

generation of mug lfnaging systems. During this partnership, Pacer Infotec Inc. seamlessly 

integrated an algorithmic face-recognition engine into its exisung MngMaatEh identification-imaging 

product In addition to sear- for suspects based on physical characteristics, Santa Ana Police 

Depamnent can use photographs, composite drawings, and video surveillance dips as the 

template image and sort the resulting images into similar and dissimilar images. This technology 

assists invesbgators in identifjmg suspects by focusing on the most probable set of unages. 

In order to properly stress test the system and assess its overall usability, Santa Ana Police 

Department’s existing data was imported into the MugMatch environment After analyzing Santa 

Ana Police Department’s current mug imaging system’s data structure, Pacer Infotec Inc. 

designed and tested an import utility that successfully transferred all surty thousand mug data 

records and unages into MggMatcb. Since the Phantomm face recognition engine relies on 

algorithmic mathematical computations, the graphs denoung the three main facial characteristics 

of an mage: left eye, nght eye, and mouth, needed to be automatically generated. A function was 

created to generate all 60,000 approximate face-findmg Phantomas graphs and successfully 

executed 

The next phase entailed training investgators on how to effectively use MngMdh. A half-day 

course wa~ provided in-house and come materials and user guides were distributed to students. 

A Santa Ana Police Department investigator was appointed as the MngMaatCh system administrator 

and took on the role to lead the system evaluation effort. During this phase, database cleanup 

efforts were made to fix exlsang mug images of individuals whose head was not photographed in 

an upright position and verify the automated placement of Phantomas graph cross points. As the 

Santa Ana Police Department‘s MngM&b system administrator became an expert user of the 

system, several enhancements were suggested to Pacer Infotec Inc. project staff members. Many 

of the valuable suggestions were designed, programmed and implemented into the latest release of 

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U.S. Department of Justice.

of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
sev& test cases were issued to test the efficiency and accuracy of the system The volume of 

data, approximately 60,000 mug records, (over 3 gigabytes of information) showed no sps of 

he rettimd response times. As for usability, investgators were able to access the MngA4azk-b 

system and perform inquiries and Pbantomas picture-to-picture comparisons after being instructed 

on how to create and edit qu&es and manipulate queq results. 

performance Both fast client hardware and open network throughput effect 

D- the evaluation process, MngMaatch proved to be a useful tool in assisting investigators in 

idaaf)mg a suspect It enables investigators to use a %tal image, dgd composite sketch, or a 

frame captured from a surveillance video and automatically sort the images into similar and 

&SS& faces. It lets investtgators focus on the most probable set of lfnages and quickly create 

high-qdty MngMatcb lineups. In closmg, the majority of the test cases issued revealed that the 

system’s ranking capabiltty was able to identify the true image match of a template’s %tal 

composite sketch within the top 5 percent on average. This project has proven Mughhtcb to be an 

advantageous tool to any investigation. 

2.0 Objective of MugMatch Software 

The objective of Mnflatcb is to assist law enforcement officials with suspec~nage booktng, 

witness Identification of suspects, and investigative work. It efficiently enables forensic 

investigation agencies to maintain a central repository of color images, physical descriptions, 

personal Identification, and arrest information of individuals tracked by the agency. W~th this 

information, agenaes can search and identify unknown suspects by using MngMatcbS robust 

textual query feature, coupled with the hgh-tech Phantoma face-recognition we. 

In a suspect bookmg, descriptions using standard termiflology are entered by tmined law 

enforcement offids. MngMatcb expedites biographical data entry by allowing customized pick 

lists and auto-fill data fields. Electronic image capture devices create high-quality photo unages. 

MngMatcb can capture and store an unlimited number of images and types of images for a single 

suspect record 

MngMatcb provides a use,r-&iendly case management environment It gives law enforcement 

offiaals the abiltty to search rapidly through mug lfnages by issuing robust textual database 

inquiries for suspects. The search capability allows invesagators to include various types of 

physical descriptions, including tattoos and aliases. Furthermore, a range of values may also be 

associated with the seatch criteria, such as “Age Today between 25 and 30” or “Hair Color is 

either Brown or Sandy”. The case management environment enables agencies to generate hgh 

quality suspect lineups in quick response to queries. Case notes may be recorded and retrieved 

throughout an investigation. For easy access, additional evidence such as photographs, composite 

sketches, or video sW&ce chps can be stored to a case, Information regardmg witnesses and 

interview sessions may be entered and also stored to the related case. In addition to its textual 

database query capabjhies, MkgMd offers a remarkable face-recognition engine. This powerful 

picture-to-picture search engine, Pbanhmm, is embedded in the MqjMajA environment 

phantomar is an automatic facial comparison and identification-imapg engine. A suspect 

idm&cadon task often began with a composite sketch, which led to a witness loo@ through 

Pssibly thousands of images. This task has proven to be a tiresome and time-consuming 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
responsibility. Phantomas takes an input image, either a facial image, a &tal composite sketch, or 

a he captured from a survedlance video, and automatically sorts the images in the A4ngMak-h 

database into similar and dissimilar faces. Therefore, the witness can focus his/her attention on 

the important details. 

Pbanfumas utilizes neural face-recognition algorithms that permit rapid response times. Pbankmas 

is capable of seard.lmg through l0,OOO images in approximately five minutes. A large database is 

likely to contain duplicate images. Phantomas greatly simplifies database administration since it 

detects duplicates through its face comparison capability. 

Phanzbmas operates by detecang the face within an image. It then places a “graph”, a right-angled 

grid, across the face. Each graph will contain nodes that axe the cross points representing the 

charact&tic features: left eye, right eye, and center of mouth. The Mq$fa,%-h user, a person who 

accesses the system, may override the system generated cross points and manually place the cross 

points on a facial image to ensure accutacy. These features are calculated using mathematical 

operations. The results are stored in the MugMatch database and will be used in obtaining the 

qualitative characterization of that face. They are of mathematical-abstract nature; therefore, it is 

not possible to reconstruct a face out of the graph values or to recognize pamcular biological 

features @e. a big nose or a sd mouth), Only the whole charactefistic of the face is evaluated 

and not apparent changes such as whether the person has a beard or no beard, glasses or no 

glasses, or even a new hairstyle. 

2.0.1 MugMatch System Architecture 

The AlzgA4ah-b sohare communicates with the MugMatcb database. The Mugllah-b data resides 

on a desrgnated database server. The server is in constant operation and communicates to 

AhgAlatcb client workstations via local or wide-area network links. The MugMatcb system contains 

several basic components: 

Capture station enters suspect information and captures mug images. 

Retrieval station searches the MugMatch database by specrfying various descriptive 

characteristics of a suspect and examining the results. 

Update station enables information to be modified. 

Administration station performs administrative duties for the caretakers of the 

MugMatch system. 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
Printer Database Server Retrieval Station 

Area Network 

- 

Capture Station Administration Update Station 

Station 

In smaller implementations, a site may choose to just use a single workstation for retrieval, 

updates, and admimaration. The capture station differs from other components since its 

configuration includes a dqgtal camera. 

3.0 Project Environment 

The following section sbtes the purpose and describes the environment of the research and 

development project 

The project consisted of developing, testing, implernenung and evaluating a state-of-the-art mug 

imaging system for the Investigtions unit of Santa Ana Police Department The project entailed 

developing and testing a robust textual search capability coupled with a sophisticated face 

recoption engine. The Phanfomas face-recognition engine utilizes neural face recognition 

algorithms enabling images to be sorted into similar and dissimilar faces. 

3.0.1 Statement of Problem 

In the last decade the city of Santa Ana has incurred significant demographic changes. Santa Ana’s 

dramatic demographic change is also contributed to the influx of immigrants. Santa Ana‘s clapme 

population has also increased since it is home to the majority of Federal, State, and private 

agencies providing social and governmental services to Southern California communities. With 

over 300,000 residents and changrng demographics, Santa Ana‘s ability to provide effective police 

and social services to the community is continually challenged 

A police investigator may investigate several related crimes. Invesugations often involve searching 

for suspects in a mug shot database. Due to the hlgh volume of unages in Santa Ana’s ongrnal 

mug database, this could make the identikition task tedious for witnesses, victims and 

investigators. After viewing a few hundred similar images, a person’s attention span wiU most 

likely dwindle. 

4 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
Many businesses have attempted to prevent crime by installing video surveillance cameras. 

Sometimes an inveswtor is able to use the suspect surveillance video clip. For cases where no 

photograph evidence exists, an investgator may rely on a composite sketch based on the physical 

description given by a victim and witnesses. The video surveillance clip or composite sketch is 

displayed among other law enforcement officials at roll call briefings, perhaps circulated among 

other law enforcement agenaes, or distributed to the media. Unfortunately, this has proven to be 

time-consuming and dows the suspect to act out additional crimes and continue to terrorize 

communities. 

The Santa Ana Police Department has expressed interest in a computer technology that assists 

investigators in the process of identifjrlng suspects in a reduced time kame than those of prior 

identifications. The MMflakb software offers investigators the ability to search for images and 

rank resulting images accordmg to SlfTLilaritY to the selected template image. The textual database 

search and face-recognition engine lets investigators, victims, and witnesses focus on the most 

probable set of suspect candidates. 

3.0.2 Santa Ana Police Department - Investigation’s System Environment 

The following section describes the environment before and after installation of the MugMatch 

software at Santa Ana Police Department 

3.0.2.1 Current Generation of Santa Ana Police Department’s Mug Imaging 

System 

The current generation of Santa AM Police Department’s mug imaging system stores and 

retrieves images and biographical data. The database server’s hardware is antiquated and the 

operating system is an outdated version of UNE. The mug shots are captured during the 

bookmg process and taken in an environment with good ltghting. Until recently, many mug 

images captured were of the individual with their head tilted shghtly to either the left or right as 

opposed to a centered and upright position. The boom 0ffice.r then enters the descriptive and 

personal information. 

‘lhe underlying database is proprietary, hence, not a commercial available produa. Due to the 

database’s complex data structure, this makes it impossible for persons other than the vendor to 

perate ad hoc reporting usmg commercial available tools. The database contains three categories 

of data: Adult, Juvenile, and Registrant Consequently, an investigator must &t select which 

database category to access before continuing. 

A total of three client workstations are available for retrieving information or aeating a person 

record. Since the dent application runs on a UNDI: platform, it is not currently possible to obtain 

the information at each investigator’s desktop computer. This has caused some lack of effiaency 

since an investigator must walk over to a mug magmg workstation and occasionally wait until 

mother investgator is finished processing a query. 

The mat lmagrng system supports a finite set of physical desuiption data elements: eye color, 

fad hair, glasses, hair color, hair length, gender, race, body height and w+t Person records 

are generated at the time of bookmg. The system limits the booking officer to capturing one 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
image per booking record. If additional images are needed to depict a tattoo or special marking, 

ad&tiod records are cleated Since multiple images may not be captuted and associated to a 

single person record, duplicate images are currently dispersed throughout the database. 

An investigator generates a group of suspects by issuing information describing the pursued 

individual. Based on the information gathered by victims, witnesses, or surveillance cameras, the 

investigator builds a query. The investigator enters the infomation into the provided dialog. 

Queries consist of text information only, which search the database for records matchmg the 

supplied Criteria. The current system is restricted to just one instance of a parti& type of 

information. For example, the query may seardl for “white males with brown hair” as oppose 

“white males with either brown or black hair”. From the resulting set, the system allows 

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Pentium Personal 

Computers l2 I 

3.0.2.2 MugMafch Environment at Santa Ana Police Department 

The followmg idenufies the delivexables made to Santa Ana Police Department at the time of 

installation: 

Dell Pentium 233 - server has 128 MB RAM and client has 32 

MB RAM. Both include monitors, network cards, controller 

cards. video caDture boards. 

I Qty I Item I VendodModel or Remark I 

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Database software 

Laser minter 

I Sybase SQL Anywhere with 4 user license. 

1 LexMark ODtra C 

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Scanner Hewlett Packard Scanjet 

Video camera Sony CCD-TR86 

VCR Sonv SLV-685HF 

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MugMatch training & Class material and a user guide was supplied to each student 

SURDOff 1 who attended the course. 

Frame grabber integral Flash Point 128 Light 

N.Monitor 20” Mitsubishi CS-20103 

MusMatch software Includes online help text. 

For evaluation purposes, only two workstations were needed: a database smer and client 

workstation. The database smer is solely used as the central MugMatch data repository. The dent 

workstation is used to access and edit information. The database server and client workstation 

both run Microsoft NT workstation. Both are connected to Santa Ana Police Department’s local 

area network via TCP/IP. Throughout the duration of the sohare evaluation period, several 

trips were made to Santa Ana Police Department in effort to upgrade the MrgMakb software and 

provide assistance to invesngators. 

3.0.2.2.1 MugMatch Evaluation - Phase I 

Phase I of the project entailed analyzing the current mug imaging system’s data structure and 

Unpomng the data into a smgle MrgMatcb database. Since the current mug imaging system is 

based on a proprietary file sttucture, a custom import utility was developed so the three categories 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
of data could be successfdly transferred into a Sybase SQL Anywhere MugMtch database 

structure. After developing and testing the import utility, all of Santa Ana Police Department's 

sixty thousand mug data records and images were successfully exported into the MugMatcll 

database. 

Upon exporting the data into figMakh, the Phantomas graphs needed to be defined This entailed 

modtfplflg the system administrator's application, Maint, by des- and programmkg a 

function that automatically calculates the Phantomas graphs. This function generated an 

approximate face-finding Phanhas graph for all sw thousand images in the MagWh database. 

3.0.2.2.2 MugMafch Evaluation - Phase I1 

Phase I1 of the project consisted of providmg trainmg to investigators on how to use MagMatch. 

In addition to the user guide, a tialf-day come was structured to train invesagators. Pacer Infotec 

provided in-house class instruction and provided come material. The class was taught in a 

computer classroom at Santa Ana Police Department so each student could practice the exercises 

on-line. 

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3.0.2.2.3 MugMafch Evaluation - Phase 111 

During this stage of the project a MugMakb system administrator was identified and trained on 

how to become the caretaker of the system. Investigators exercised MugMatch to evaluate its 

overall usability. To ensure the system's accuracy, it was suggested that one or more individuals 

be appointed to review the Phanhmar system generated face-fin% graphs. Many of the mug 

shots captured &om Santa Ana Police Department's Cutrent mug imaging system displayed 

individual's with their head shghtly tilted either to the left or right. To obtain optimal results in a 

picture-tepicture search, the Phantomas graphs needed to be rotated to an upnght position and 

cross points redefined MtgMatch offers a utility enabling image rotation and a separate function 

€or editing the Phantomas graph. 

In effort to complete this task, Pacer Infotec adopted the task. Approximately, twenty-five 

percent of the graphs were reviewed and modified if necessary. 

3.0.2.2.4 MugMafch Evaluation - Phase IV 

Dunng this phase, the appointed system administrator, investigator Mark Strohman, became 

acquainted with fiflakb and assembled a requirement and enhancement list of features he 

thought would be useful to investigations. Pacer Infotec analyzed the list and were educated on 

the type of features that would make investiptors more efficient in domg their detective work. 

Pacer Infotec designed, programmed and implemented several new features suggested by Santa 

Ana Police Department's MngM&h system administrator. The following summarizes the features 

implemented in the latest Mufl&h release: 

It is now possible to create a query that matches the description of a selected image in a query 

results viewer. From the speed menu, choose Q-eate AutoQuq" and a new query will be 

created with a description that matches the selected image. The query property dialog is 

opened to pennit editing of the new query. When the query is saved, it is associated with the 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
a 

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case from which the query results originated. The default name of the query is "AutoQuery - 

NAME" where NAME is the name of the person horn which the query is derived There are 

a number of items that can be included in the system-generated query. The user is given the 

opportunity to select these items when the AutoQuery is hrst created 

The person locator dialog was modified to provide more flexibility. The new person locator 

capability allows the user to search for several charaaeristics simultaneously, includmg last 

name, first name, date of b& gender, SSN, driver's license, race, and age. The results are 

displayed in a list which is appended to the locate ddog duing the search. For each entry in 

the result list, details can be obtained. Optionally, a locator query can be executed which 

shows details or images according to the Options setting. 

It is now possible to rearrange the images in a lineup builder using drag and drop techniques. 

To move an image from one frame to mother, click on the lfnage with the left mouse button, 

hold the button down, drag the mouse to the frame where the image is desired and release the 

mouse button. If you drag one image on top of another, the onpal image is cleared and the 

image being draged replaces it 

A new feature has been added to case viewer. It is now possible to capture and save lfnages so 

that they are associated with a case. An additional branch appears in the case viewer to display 

these images. 

In the query results viewer, it is now possible to easily skip to the next/previous page 

containing a suspect There are two new buttons in the query result viewer toolbar that are 

used for thts purpose. 

A progress bar has been added to the Phantomar Sort and Phantomas Compare functions. It is 

now possible to cancel these operations prior to completion, in which case the associated 

query results are unchanged. 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report
i 

Gender 

Age Today 

4.0 Case Findings 

To measure how well MngMatcb performed; several test cases were issued and executed at Santa 

Ana Police Department For some scdos, composite sketches of known suspects were 

obtained from Santa Ana Police Department’s FaceKit workstation. These images were saved in a 

TLFF format and imported into a MugMakh case for effiaent remeVal If the suspect did not 

already eIcist in Santa Ana Police Department’s mug database, then a record was created and the 

actual mug shot or related photograph was scanned into the M.ugMatch database. The following 

cases reflect a sampltng of tests performed at Santa Ana Police Department 

= Male 

Between 28 and 40 years old 

Test Case 1 

~~~ 

Weight 

Hair Color 

i 

Be&n 150 and 175 pounds 

= Black 

Query panmeten: 

I Attribute I Criteria I 

1 Race I = Hispanic I 

I Height I Between 5’08” and 6’00 I 

iYumber ofmatches: 2,426, 

Phantomas tenphte sozim Facefit composite sketch image as a TIFF image. 

Result The Phantomas facial comparison ranked the suspect in position 59 out of 2,426. 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

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Test Case 1 environment 

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has not been published by the Department. Opinions or points of view expressed are those

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Test Case 2 

Attribute 

RaCe 

Gender 

Age Today 

Height 

Weight 

Criteria 

= Hispanic 

= Male 

Between 28 and 31 years old 

Betwen 5’02” and 5’05 

Between 130 and 150 pounds 

Number $m&bes: 1,287. 

Phantomas -.&e soum FaceKit composite sketch unage as a TIFF image. 

Resuk The Phantomas &cial comparison engme ranked the suspect as 25* out of 1,287 returned 

matches. 

lest Lase 2 enwonment 

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has not been published by the Department. Opinions or points of view expressed are those

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Test Case 3 

QmypanmeM 

Age Today 

Height 

I Attribute I Criteria I 

Between 21 and 30 years old 

Less than 6’00” 

Weighf 

€ye Color 

Less than 200 pounds 

= Blue 

Phantomas zkn-pkate som-c FaceKit composite sketch as a TIFF image. 

Rex& The Phantomas facial comparison engme ranked the suspect as 9* out of 129 returned 

images. 

Test Case 3 environment 

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has not been published by the Department. Opinions or points of view expressed are those

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I 

Race 

Gender 

Test Case 4 

Qmypmmetmc 

= white 

= Male 

Height Color 

Facial Hair 

I AW Class I =Adutt I ~~~~ 

= Brown or Sandy 

= Mustache 

I Eyewear I =Yes I 

Number dmatcbex 105. 

Phntomar tenphe so~m FaceKit composite sketch image as a TIFF image. 

Res& The Phantomas facial comparison ranked the suspect in the 13th position out of 105 

returned images. 

Test Case 4 environment 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

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5.0 Conclusion 

Pacer Infotec Inc is proud to have partnered with Santa Ana Police Department to create the 

p0werfi.d mug identification imagrng system, figM&h. Pacer Infotec Inc and Santa Ana Police 

Department personnel worked closely together to achieve the goal of developing, integrating, 

implementing, and evaluating the enhanced MigMazkh system. 

During the evaluation period, it has been demonstrated that AhgMa&h is a useful tool in assisting 

investigators in idenafplng a suspect Several time saving features such as the Phanbmas picture-topicture search, robust query editor, and new AutoQuery function lets an investigator concentrate 

on the most important details of a case. Instead of manually searching through approximately 

60,000 mugunages, figJUakb5vatious tools let an investigator review a manageable set of 

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I Of the Santa Ana Police Department mug database, a typical query wiU usually return several 

thousand images. MugMatL-hS Phanhma face-recognition engine lets the comparison search 

automatically rank the resulting images according to how sirnilat they are to the input template 

image. This spificandy reduces the amount of time spent analyzing each image, hence 

decreasing the chance of becoming faugued The test cases performed at Santa Ana Police 

Department revealed that the system's face recognition capability can locate the true image match 

using a %tal composite sketch within the top 5 percent of returned unages. This project has 

proven MUgMkb to be an advantageous tool to any investgation. 

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of the author(s) and do not necessarily reflect the official position or policies of the

has not been published by the Department. Opinions or points of view expressed are those

This document is a research report submitted to the U.S. Department of Justice. This report