Brochure

Visual ServerVideo and Image Analytics Overview

Brochure
Visual Server

All-In-One Image Processingand Analysis Technology

With the rapid rise of mobile devices, visual content has become extremely valuable for businessintelligence. With smart image recognition technology, seemingly low value pictures, such as “selfies,”
can reveal a great deal about people, their interests, and their environment. While most organizations
collect and store images, they do not make use of this valuable resource because of the significant
manual efforts required in processing and analysis such data.
OpenText™ Visual Server automates the processing and analysis of image files. It offers a unique combination of a rich set of features, extensive
image file type support, and a high level of accuracy in an end-to-end
solution. Its capabilities can be grouped into the following categories:
Opticalcharacterrecognition
Description

ExampleFeatureDescription

ObjectObject recognition

Detect specific objects such as
corporate logos or product packaging
Locate generic objects such as cars,people, chairs, trucks
Categorize different classes of objects
depicted in the image
Detect changes in images before andafter versions
Analyze dominant colors of an image
Automatically read number plates(license plates) of vehicles
Recognize the make, model, and colorof a vehicle
Convert text in image files into text files

Object detection
Image classification

Image
classification

Objectrecognition

Detect objectsof particular
categories are
in an image orclassify objects
by featureThis image
There areThis image
has text “Thethree faces in contains a car,quick brown fox this image.
a building, and ajumps…”
pedestrian.

Identify aspecific object
is present

Extract text
from imagesof machineprinted text

TypeObject
detection
Detect thatan object ispresent

The logo
shown here is
the OpenText
logo.

Change detection

Vehicles

Text

Color analysis
ANPRVehicle make, model,and color
Optical character
recognition (OCR)
1D and 2D barcode
detection

Visual Server offers the following high-level features to help make senseof image data:

ScenesScene analysis

TypeFeature

Description

Other

Keyframe analysis
Image editing

HumanFace detection
Face recognition

Detect faces in an image
Train and compare faces against a
database of known faces
Analyze faces in images to determine
demographic information
Detect clothing and dominant colors ofclothing including skin tones

Face analysis
Clothing analysis

2Detect text on images such as subtitles
on a frame of a video
Detect barcodes from over 20 barcode
types, including ISBN, PDF417, and data
matrix
Detect atypical events in surveillance
videos such as running, illegal crossings,
and traffic violations
Detect scene transitions in video
Blur a region of the image, draw an
outline around a region of the image,or crop an image

Supported image types include:■ WAVE (Waveform Audio) (.wav)■ TIFF■ ASF (Windows media) (.asf, .wmv)■ JPEG■ Raw AAC (.aac)■ BMP■ Raw AC3 (.ac3)■ PNG

Additionally, Visual Server can also ingest video from cameras and thirdparty video management systems such as:■ GIF■ MJPEG video streams■ ICO■ DirectShow device■ PBM■ Milestone XProtect

■ PGM
■ PPM

Who Benefits?

Additionally, with the help of OpenText KeyView, Visual Server can support
document formats including:™

■ PDF■ DOC and DOCX■ XLS and XLSXMany of the Visual Server media analytics features have traditionallybeen connected to specific industries, for example, facial recognition
for security or barcode reading for consumer merchandising. However,as cameras and digital images continue to reach more areas of everyday life, there is the potential for all businesses to leverage the power ofimage analytics. The ability to run all facets of image analysis together
leads to a more efficient and improved workflow.

■ PPT and PPTX
■ ODT
■ RTF

Supported video codecs include:
Video Codecs■ MPEG-1■ MPEG-2■ MPEG-4 part 2■ MPEG-4 part 10 (Advanced Video Coding) (H.264)■ MPEG-H part 2 (High Efficiency Video Coding) (H.265)

Features
Visual Server analyzes and edits image files. Visual Server can be used
to process large repositories of images and extract information fromthem. In particular, Visual Server can be used to:■ Detect faces, recognize faces, and analyze faces to extract

facial attributes■ Recognize text in scans and photographs of machine-printed text
■ Classify images into various object categories■ Locate objects belonging to generic categories within images■ Recognize specific 2D and 3D rigid objects such as movie posters

and company logos■ Windows media 7■ Edit images, crop images, or blur images■ Windows media 8■ Detect and read barcodes, including QR codes

File Formats■ MPEG packet stream (for example .mpg)■ Detect most dominant colors present in an image, including■ MPEG-2 transport stream (for example .ts)

■ Automatically recognize number plates on vehicles■ MPEG-4 (for example .mp4)■ Recognize vehicle make, vehicle model, and vehicle colors

www.microfocus.com/opentext

skin tones

3Brochure
Visual Server■ Detect atypical events in CCTV camera footage■ Extract keyframes from video■ Generate image hashes to compute approximate image similarity

Face Analysis
A face can also be analyzed for specific traits. Visual Server can estimate the approximate age range (baby/child/young adult/middle age/elderly), ethnicity, gender, and expression of the person being analyzed.

based on color
This section covers the Visual Server features in more detail.

Face Detection
Face detection finds faces in a given image. Visual Server returns thecoordinates of a detected face in a photo, as well as the position of key
facial features such as the eyes.

Object Recognition
Visual Server can be trained to recognize specific objects or complex
patterns in analyzed images. For example, a user can train a databaseof corporate logos to combat copyright infringement. When a picture
is analyzed, Visual Server can report if it has found any matching logos
from its training set. The objects can be 2D or 3D objects in images.

Figure 3. Logo and object recognition
Figure 1. Face detection and analysis

Face Recognition
In addition to finding faces, Visual Server and its facial recognition features can also compare the detected face to a database of known individuals. The matching threshold can be adjusted to suit different needs.
Visual Server face recognition technology is comparable to other leading face recognition vendors.

Figure 2. Face recognition

4

Image Classification
Image classification automatically categorizes objects that appear inimages based on previous training. For example, Visual Server can betrained to recognize vehicle categories such as cars, trucks, and motorcycles. This allows users to sort images as they are analyzed and toflag certain objects, if necessary. Visual Server also provides pre-trainedclassifiers that can label images with existing categories, so that it becomes easier to automatically tag large collections of images.

Figure 4. Image classification using trained shapes

Optical Character Recognition (OCR)
Optical character recognition is used to extract text from image files.
The use of OCR on scanned or photographed documents, pictures, orphotos facilitates the conversion into a computer-readable format to
make it easier to store and search the documents. Given an input image,
Visual Server can return the identified text, the confidence score, andthe region of the image the text was read from. The detection region canbe bound to certain areas to decrease noise from the rest of the image
and accuracy can be fine-tuned to the position of each character. VisualServer supports all major languages and font types for OCR. A full list oflanguages and fonts are available in Appendices A and B.

Figure 6. Visual Server is able to detect and read barcodes

Object Detection
Object detection can be used to locate instances of objects that belong
to known, predefined classes. For example, one could detect all pedestrians, vans, and cars that appear in a video.

Automatic Number Plate Recognition (ANPR)
Detect and read the number plates (license plates) of vehicles in images or video. Number plate recognition has many applications; youcan detect stolen and uninsured vehicles, and monitor the length ofstay for vehicles in car parks.

Vehicle Make, Model, and Color Analysis

Figure 5. Text is captured from an advertisement using OCR

BarcodeVisual Server has robust support for detecting one-dimensional andtwo-dimensional barcodes, including QR codes in an image. It can return the data contained in the barcode, as well as barcode type andregions. The following barcode types are supported:
PDF417

Data matrix

ISBN (orEAN-13)

SBN-2 (orEAN-2)

I25

ISBN-5 (orEAN-5)
Codabar
UCC/EAN128 (orGS1-128)

Code-128

Code-93

Code-39

IATA 2/5

Patch CodeEAN-8Matrix 2/5
UPC-A

Datalogic 2/5
UPC-E

Industrial 2/5

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Visual Server can help identify the make, model, and color of a vehicle
captured during number plate recognition. Vehicle model recognition
can help law enforcement identify stolen vehicles.

Scene Analysis
Scene analysis detects atypical events that occur in video. This can beused to monitor video streamed from CCTV cameras, to assist with thedetection of potential threats, illegal actions, or alert human operators
to situations where help is required.

Keyframe Analysis
Visual Server can help identify when there are significant scene changes
within a video. This can be useful for creating thumbnail photos or timesnapshots.

5Brochure
Visual Server

Change Detection

Scalability and High PerformanceVisual Server can help identify when there are changes within a scene.
For example, one may wish to look for objects that have disappeared,
new objects that have appeared, or objects that have moved to different
parts of an image or scene. This can be used to find defects in imagesof equipment or create alerts for suspicious movements within a surveillance application.

Color Analysis

Visual Server can run several tasks at once in parallel and take full advantage of the available hardware. Tasks can be distributed across several
Visual Servers. Visual Server then queues the tasks and runs them in orderor multiple tasks at a time. The user can check on the progress of each task,
kicking off additional tasks, if necessary, enabling better batch processing and more complicated workflows. Multiple Visual Servers can talk to
a common shared database or share data across different databases, sothat users get complete flexibility.

Visual Server also includes basic photo analysis functionality, including
reporting picture size, color dominancy, and palettes. This is often usedin conjunction with object recognition when automating processes that
require identification of photo subjects such as cars.

Visual Server can accelerate processing by using a GPU. If multiple
GPUs are available, one can run multiple Visual Servers on the samemachine.

Image Editing
Many analysis tasks return regions of interest. Visual Server provides
facility to crop an image to a desired region, blur a region of the image,or draw an outline around a region in the image.

Stand-Alone Server Architecture
Visual Server is a stand-alone media analytics server that uses theOpenText™ Autonomy Content Infrastructure (ACI) Client API to communicate with custom applications. It allows data to be retrieved over
HTTP using XML and can adhere to SOAP. It supports both synchronousand asynchronous actions (see the section on scalability).

Applications
ACI
API/SOAPACI
API/SOAPACI
API/SOAP

To improve performance in a production environment, Visual Server
supports both synchronous and asynchronous actions, and can be
distributed for horizontal scaling.
With a synchronous action, Visual Server runs the task immediately andreturns a result when the action is complete. Asynchronous actions allow a user to send multiple tasks all at once, returning a task ID/token foreach job. In large media analytics systems where a very large numberof documents need processing, it is possible to distribute work among
multiple instances of Visual Server.

Out-of-the-Box Operation
Several of our analytics come with pre-trained models allowing outof-the-box operation. We provide pre-trained models for facial demographics, image classification for over 1000 common classes, objectdetection, pedestrian detection, face detection, vehicle make detection, and vehicle color detection.

Comprehensive Analytics

HTTPHTTP

HTTP

Visual Server offers full functionality in a single product. A unified solution allows for greater freedom in workflow design and faster integrationand deployment. As a result, it is easier to use multiple media analytics using Visual Server and no time is wasted getting multiple vendors’
products to work together. A unified solution makes it easy to perform
complex analytical queries spanning multiple features.

Summary

Visual Server
Figure 7. Visual Server architecture

6

In the modern information age, organizations must move beyond merely
accessing data to figuring out how to analyze and make sense of vastquantities of data. When businesses can understand information in realtime, it becomes possible to make intelligent, data-driven decisions that
can have a positive effect on success rates. Image data is one format
that is often stored but not analyzed beyond its simplistic metadata because of the difficulty that traditional technologies have in understanding the vast amount of information held in a single picture. With VisualServer, organizations can improve this increasingly prominent data set
to operate at full potential and with greater agility.
Learn more at
www.microfocus.com/richmedia
www.microfocus.com/opentext

Appendix B
Supported Special Font and Character Set Codes for OCR
FontGeneral
Arial Narrow
OCR-A
OCR-B
E13B
Farrington 7B
Old-Style Times
Custom font used for Bloomberg terminal GUI

Appendix A
Supported Languages for OCR
Latin alphabet

Cyrillic alphabet

Other alphabets■ Afrikaans (af)■ Bulgarian (bg)■ Greek (el)■ Esperanto (eo)■ Serbian (sr)■ Hebrew (he)■ Italian (it)■ Macedonian (mk)■ Arabic (ar)■ Portuguese (pt)

■ Ukrainian (uk)■ Persian (fa)■ Basque (eu)

■ Russian (ru)

■ Urdu (ur)■ Estonian (et)■ Japanese (ja)■ Irish (ga)■ Simplified Chinese (zhs)■ Romanian (ro)■ Traditional Chinese (zht)■ Catalan (ca)■ Finnish (fi)
■ Latin (la)■ Slovak (sk)
■ Croatian (hr)■ French (fr)
■ Latvian (lv)
■ Slovenian (sl)■ Czech (cs)■ German (de)■ Lithuanian (lt)
■ Spanish (es)■ Danish (da)■ Hungarian (hu)■ Maltese (mt)■ Swedish (sv)
■ Dutch (nl)
■ Icelandic (is)■ Norwegian (no)■ Turkish (tr)■ English (en)■ Ido (io)■ Polish (pl)■ Welsh (cy)www.microfocus.com/opentext

7Connect with Us
OpenText CEO Mark Barre­nechea’s blog

263-000021-001 | O | 05/23 | © 2023 Open Text