Demonstration of visual based and audio-based hci system

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 05 Issue: 04 | Apr-2016, Available @ http://ijret.esatjournals.org 342
DEMONSTRATION OF VISUAL-BASED AND AUDIO-BASED HCI
SYSTEM
Priya Rathore1
, Anjali Khatri2
, Aparna Pushpad3
, Swekcha Jain4
1
Assistant Professor, Electronics and Communication Department, Medi-caps Institute of Science and Technology,
Madhya Pradesh, India
2
UG student, Electronics and Communication Department, Medi-caps Institute of Science and Technology, Madhya
Pradesh, India
3
Pradesh, India
4
Pradesh, India
Abstract
This paper is an attempt to provide a bird’s eye view to the concept of Human Compute Interaction (HCI). The intention is to
focus on the uni-modal architecture of HCI; especially the HCI system based on visual-based and color-based communication
channels viz-a-viz color recognition and speech recognition. We have developed a Graphical User Interface (GUI) for the same
using MATLAB; one push button assigned for color input (through webcam) and the other push button assigned for speech input
(through microphone). In color recognition, primary colors i.e. RGB are detected in frames captured in real time or images
uploaded offline. Subsequently, desired operation is executed (we have set commands to open D drive). In speech recognition,
audio input through microphone is compared with a pre-stored audio file and then an operation is performed automatically (here,
we have set commands to open Google web browser). The respective algorithms of these two processes have been described with
flow-charts and snapshots of MATLAB results have been displayed.
Keywords: Human Computer Interaction, Uni-Modal Architecture, Color Recognition, Speech Recognition
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1. INTRODUCTION
In earlier days, computing was only restricted to research in
scientific and astronomical laboratories. Only highly trained
specialists of these fields could handle computers. And also,
in the name of computers, there were massive expensive
computing machines which required programming and
functioning by skilled veterans. But today, we can make out
that from gigantic unhandy electronic machines to slim
laptops and i-pads in our bags, computers have come a long
way! Unlike the 1980s, majority of computer users today
have not received any specialized training in computer
programming, though they can effectively interact with
computers for a broad range of utilities.
Human Computer Interaction (HCI) is the study of the
„interaction‟ between humans and computers. The definition
doesn‟t end there. The word „interaction‟ used above must
be clarified with the phrase „easy interaction to obtain
effective and desired results‟. It is a study of the ways in
which man handles or utilizes computer technology in order
to influence his life with a target of simplifying things. It is
about creating a software or any other technology that
people will want to use, will be able to use and will find
effective when used. The Curriculum Development Group
of the ACM Special Interest Group defines HCI as a
„discipline concerned with the design, evaluation and
implementation of interactive computing systems for human
use and with the study of major phenomena surrounding
them‟.
As evident from above, HCI can be defined in numerous
ways. But all the definitions hover around the concept of
„interfacing‟. Utilizing computers has always required easy
interfacing. Over a few decades, the methods of interfacing
with computers have changed drastically. Thus, HCI has
become a ubiquitous research area attracting many
professionals from various fields. The main focus though
has always been on functionality and usability. Both of these
terms are interconnected. Functionality of a certain system is
defined as the range of operations that can be run or
performed, i.e. the services that it provides to its users.
However, functionality can only be considered when the
system can be efficiently and adequately utilized by the
users. Here comes the issue of usability. Usability is a
quality attribute that inspects how easy user interfaces are to
use. In short, it can be defined solely as ease-of-use. These
two attributes jointly determine the importance and need of
a certain HCI system.
1.1 Architecture of HCI Systems
An HCI system is usually defined by the behavior and
diversity of its inputs and outputs. These inputs and outputs
are the key attributes which form the basic outline of the
way in which interaction is occurring between human and
the computer. This is the very aspect defined by the
architecture of an HCI system. It can be classified into two
types:

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1.1.1 Uni-modal HCI systems
An HCI system which depends on only one genre of inputs
is known as a uni-modal HCI system. The independent
channels are also known as modality. Thus, a uni-modal
system comprises on one modality. A lot of new ways to
provide input to HCI systems have been evolved; for
example, visual-based, audio-based, sensor-based, sixth
sense-based etc. In this paper, we intend to cover only uni-
modal HCI systems; especially visual-based and audio-
based. These are expounded later on in other sections of this
paper.
1.1.2 Multi-modal HCI systems
In these types of HCI systems, different modalities are
engaged, i.e. there are a variety of communication channels.
A combination of two or more modalities can be used to
design a multi-modal HCI system
1.2 Literature Survey
Learned basics digital image processing concept from the
book of digital image processing by gonzalez and woods
[1]. The overview of HCI(Human Computer Interaction) is
studied from International Journal On Smart Sensing And
Intelligent Systems, VOL. 1, NO. 1, March 2008 [2]. Color
detection methodology has being taken from Real-Time
Object Tracking Using Colour Feature, Basic Geometric
Shape And Primary Colour Detection Using Image
Processing On MATLAB [3] [4] [5]. Speech recognition
has been included from An HCI Speech-Based Architecture
for Man-To-Machine and Machine-To-Man Communication
in Yorùbá Language[ 6]
1.3 Color Detection and Speech Recognition
We are performing two techniques for color detection that
are offline and online. Offline color detection can be done
by selecting predefined colors in the computer, for this we
have taken snapshots of blue green and red color in
rectangle shape and for online color detection webcam is
used to capture real time image of the object and basic color
are being recognize and message is being displayed in both
the cases of offline and online.
Speech is a means of communication. When we talk about
interaction with computers, intially it started with devices
like mouse, keyboard etc via electromechanical means,
eventually it upgraded to a more natural way that is speech;
and for this we need a speech recognition system. In this
paper we have described about the application of the speech
recognition system. With the use of speech recognition we
have opened web page by browsing certain sound which we
have already stored; detection of the sound is done in real
time and if it is matched with the stored sound, desired work
is done according to the back end programming. Speech
recognition is a hierarchy of level in which the process is
compiled.
2. ALGORITHMS
The algorithm for color detection is:
Step1: Graphic user interface (GUI) is made with two push
buttons, namely, offline and online as shown in fig.2.
Step2: When we press offline: three colors already stored in
our computer‟s memory is displayed and by clicking on any
of the color message is further of red, blue, or green as
shown in fig.3.
Step 3: By pressing online named push button we will
observe that web camera will start and the process will start
to detect the basic colors as shown in fig.5.
Step 4:In case of offline color, the colored image is being
converted into gray scale and then the gray image into
binary .
Step 5: In case of online color, web camera is configured
and frames are set to manual and returned type color space
to RGB.
Step 6: By switching for different colors we apply same
algorithm for three basic colors.
Step 7: Initially it is converted into gray color and then
filtering is done to avoid noise after this the image is being
converted into black and white.
Step 8: Then the region properties like Bounding Box and
Centroid are used.
Step 9: Plot the image and message box showing the color
detected.
Algorithm for speech detection:
Step 1: Record the sound using a microphone for the desired
time as already stated in the programme.
Step 2: Save the sound recorded as shown in fig.7.
Step 3: During speech recognition, real time speech is
recorded; and is checked with the already recorded sound.
Step 4: As soon as sound is matched with the pre-recorded
sound, the work alotted to that particular sound is done (
opening of D drive and web browser page) as shown in fig.6
and fig.8.

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MATLAB results:
Fig 1. GUI of human computer interaction system
Fig 2. Color acquisition GUI
Fig 3. Offline color acquisition from database

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Fig 4. Outputs of Color recognition in offline mode
Fig 5. Real time color detection
Fig 6. Output as local disk D
Fig 7. Speech acquisition GUI
Fig 8. Output as google web browser
3. CONCLUSION
Human computer is basically description of ways in which a
man can interface with machine in the most efficient and
easiest way. This technology has reached to an extent where
an individual just have to make an gesture to perform a
particular task, like in sixth sense technology just an gesture
of taking a picture results in an image, also words from hard
soft can be transferred to soft copy for further processing, in
addition to this just a plane sheet of paper can help user to
play a racing game making it very interesting and easy. Our
day to day life activities can be automated. This made us
work on the project similar to this technology. We have
researched regarding speech recognition and color detection.
It holds immense importance in today's era; boon for people
with disabilities making their work easier and saves time as
we would not have to go through a large set of steps. Instead
we can do it by just speaking a word. One of the significant
feature of speech recognition is rhythm, which may generate
a conspicuous change, thus we need to look after it. It can be
removed effectively with the use of concatenative synthesis.
Storing words and their attributes for efficient detection
which may slow down the system due to large database. In
color recognition, lightning effect play a major role. In order
to identify color correctly. We need to have proper light and
less or no noise background. We have achieved 98%
efficiency in color detection with considerable noise,
thereby getting correct results. The major drawback is that
the programming required is very complex.
REFERENCES
[1]. Digital image processing using Matlab -Gonzalez
woods & Eddins.
[2]. Fakhreddine Karray, Milad Alemzadeh, Jamil Abou
Saleh and Mo Nours Arab,”Human-Computer
Interaction: Overview on State of the Art”,
International Journal On Smart Sensing And Intelligent
Systems, Vol. 1, No. 1, March 2008.
[3]. Shubham Srivastava, Pratibha Singh, “Real-Time
Object Tracking Using Colour Feature”, International
Journal of Innovative Technology and Exploring
Engineering (IJITEE), ISSN: 2278-3075, Volume-3,
Issue-8, January 2014.
[4]. Shambhavi Vijay Chhaya, Sachin Khera, Pradeep
Kumar S, “Basic Geometric Shape And Primary
Colour Detection Using Image Processing On Matlab”,
IJRET: International Journal of Research in
Engineering and Technology eISSN: 2319-1163 |
pISSN: 2321-7308.

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[5]. D.Senthamaraikannan, S.Shriram, Dr.J.William,” Real
Time Color Recognition”, International Journal Of
Innovative Research In Electrical, Electronics,
Instrumentation And Control Engineering, Vol. 2, Issue
3, March 2014.
[6]. Akintola A. G., Ibiyemi T. S. Adewole K. S., “An HCI
Speech-Based Architecture for Man-To-Machine and
Machine-To-Man Communication in Yorùbá
Language”, Computer Engineering and Intelligent
Systems, ISSN 2222-1719 (Paper) ISSN 2222-2863
(Online), Vol.6, No.7, 2015.
BIOGRAPHIES
Priya Rathore, Assistant Professor,
Electronics and Communication
Department, Medi-caps Institute of Science
and Technology, Madhya Pradesh, India
Anjali Khatri, UG Student, 8th semester,
Aparna Pushpad, UG student, 8th
semester, Electronics and Communication
Swekcha Jain, UG student, 8th
semester,

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