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(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
Image Processing Algorithm
JPEG to Binary Conversion
Mansi Gupta Meha Garg Prateek Dhawan
Dept. of Computer Sc. & Dept. of Computer Sc. & Dept. of Computer Sc. &
Engg., Engg., Engg.,
Lingaya’s University, Lingaya’s University, Lingaya’s University,
Faridabad, Haryana,India Faridabad, Haryana,India Faridabad, Haryana,India
manasigupta18@gmail.com, mehagarg.be@gmail.com prateek.3212@gmail.com
Abstract – The JPEG processing algorithm works best As for the LAB colour space, L* stands for
on photographs and paintings of realistic scenes with luminance, a* is the red-green axis, and b* is the
smooth variations of tone and colour but is not well blue-yellow axis. The asterisks were added to
suited to files that will undergo multiple edits. The
differentiate CIE from another L,a,b model.[3]
direct conversion of jpeg image into binary format is
Although CIE L*a*b* has a large color gamut and
very low in efficiency. In this paper, the process of
conversion of jpeg image to binary image is being
is considered as the most accurate colour model, it
done in a step by step manner, without using direct is often used as a reference only or as an
inbuilt function of jpeg to binary in MATLAB. As the intermediary for colour space conversion.
binary image is used for comparison purposes, the
jpeg image is converted into LAB format to make the II. VARIOUS METHODS FOR
luminance scale perceptually more uniform, so that COMPUTING BINARY IMAGE
the procedure becomes more efficient.
The JPEG image can be converted into Binary
Keywords: LAB, Binary image, sign language
image by writing codes using C# or Visual Basic.
I. INTRODUCTION
This conversion can also be implemented by
JPEG (named after the Joint Photographic Experts conversion of RGB into grayscale first and then
Group who created the standard) is a commonly into binary.
used method of lossy compression for photographic
It can also be done with the help of an inbuilt
images. [1]
function in MATLAB. The function is
im2bw(RGB, level). Applying this function on the
Another format is the binary format which has
image for alphabet A generates a corresponding
pixels with only two possible intensity values.
binary image in fig.1
They are normally displayed as black and white.
Numerically, the two values are often 0 for black,
and either 1 or 255 for white.
Binary images are often produced by thresholding
a grayscale or color image, in order to separate an
object in the image from the background. The color
of the object (usually white) is referred to as the Fig.1 JPEG and Binary image for alphabet A
foreground color. The rest (usually black) is
referred to as the background color. However, III. PROBLEM DEFINITION
depending on the image which is to be threshold,
this polarity might be inverted, in which case the The object is hands of the sign language useer
object is displayed with 0 and the background is which must be in fully in black when displayed in
with a non-zero value. [2] the binary image. The image in fig. 1 is not clear
and has distortions too, i.e., the hand portion is not
in black completely. This would hinder gaining
75 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
higher efficiencies in further processing of the colour axis L*, a* and b*. The image is then
image, if required. viewed in these colour spaces and the sensitivity is
tested. After testing the sensitivity, a suitable
With most gestures one-handed, signs maybe one- threshold value of L*, a*, b* or an appropriate
handed (ASL) or two handed (BSL). combination of either a* and b* or any other colour
axis is taken for formulating the binary images.
Using colours to identify users’ hands may pose
There are different set of values for detecting the
problems when there are uncontrolled backgrounds
skin and differentiating it with the background
[5] depicted in fig.5
colour.
Fig.5 Image for alphabet A
Few signs are often very similar (or even identical) Fig.8 LAB Image for alphabet A
in there manual features but differ in non-manual
After the implementation of the specified values,
features (Fig. 6)
the image can finally be converted into a binary
form
Fig.9 Binary Image for alphabet A
All those pixels that have their values in this
Fig. 6 Images for L, M, N and V alphabets
specified range are given a value of 0, i.e. white
and rest all the other pixels are given a value of 1,
IV. METHODOLOGY
i.e. black.
First the JPEG image is filtered to reduce noise and
enhance the visual quality of the input image. V. APPLICATIONS
Filtering constitutes an important part of any image
The binary images can be generated for all the
processing pipeline where the final image is
alphabets of BSL sign language and can be used for
utilized for visual inspection or for automatic
recognizing the alphabets. This would eliminate the
analysis. [4] This preprocessing helps increase the
need for sensors and other devices like digital
performance of the subsequent stages.
gloves which have been used in sign recognition
previously.
Also, it would greatly increase the efficiency for
further image processing, if required, because of
the near-perfect and low noise images produced.
VI. ADVANTAGES OF BINARY
Fig.7 Filtered Image for alphabet A
• Easy to acquire: simple digital cameras can
Then the filtered image in RGB colour space is be used together with very simple frame
converted into LAB colour space. In LAB format, stores, or low-cost scanners, or thresholding
the figure can be segmented into three different may be applied to grey-level images.
76 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
• Low storage: no more than 1 bit/pixel, often REFERENCES
this can be reduced as such images are very
[1] http://en.wikipedia.org/wiki/JPEG
amenable to compression (e.g. run-length
coding). [2]http://www.codersource.net/csharp_color_image_to_b
inary.aspx
• Simple processing: the algorithms are in most
cases much simpler than those applied to [3]http://www.answers.com/topic/cie-lab
grey-level images.
[4]http://encyclopedia.jrank.org/articles/pages/6691
/Color-Image-Filtering-and-Enhancement. html
VII. DISADVANTAGES OF BINARY [5] A multimodal framework for the communication of
IMAGES the disabled Savvas Argyropoulos 1, Konstantinos
Moustakas 1, Alexey A. Karpov 2, Oya Aran 3,
Dimitrios Tzovaras 1, Thanos Tsakiris 1, Giovanna
• Limited application: as the representation Varni 4, Byungjun Kwon 5
is only a silhouette, application is
restricted to tasks where internal detail is
not required as a distinguishing
characteristic.
• Does not extend to 3D: the 3D nature of
objects can rarely be represented by
silhouettes. (The 3D equivalent of binary
processing uses voxels, spatial occupancy
of small cubes in 3D space).
• Specialised lighting is required for
silhouettes: it is difficult to obtain reliable
a final year
M e h a G a r g ,
binary images without restricting the student at Lingaya’s
environment. The simplest example is an Institute of Mgt. & Tech.,
Faridabad, Haryana,
overhead projector or light box. India. Her areas of
interest include Image
processing and Artificial
VIII. CONCLUSIONS AND FUTURE Neural Networks. She
WORK has published a paper in
national and another in
international conference
In this paper, the threshold determined is user- during her BE level.
independent. It will produce exact binary images
irrespective of the skin colour of the sign language
user. P r a
a final
t e e k D h a w a n ,
year student at Lingaya’s
Institute of Mgt. & Tech.,
The JPEG images that have been taken for
Faridabad, Haryana, India.
processing have been clicked from a fixed distance,
His areas of interest
keeping the camera position fixed too.
include Image processing,
Future work includes removing these constraints
Artificial Neural Networks,
for distance and camera position and forming clear
Computer organization and
binary images without distortions. It will focus on
Operating System.
the extension of the developed modules in order to
support larger vocabularies and enable more
natural communication of the users.
77 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
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