CERTIFICATION WATERMARKING FOR DIGITAL
HANDHELD-CAPTURED PHOTOGRAPHY
Yves Stadler
1,2
1
CodaSystem France, 79 rue de S
`
evres, 92100 Boulogne-Billancourt, France
Yann Lanuel, Anass Nagih, Francine Herrmann
2
Laboratoire d’Informatique Th
´
eorique et Appliqu
´
ee, University of Metz, Ile du Saulcy, 57045 Metz Cedex 1, France
Keywords:
Image watermarking, Handheld device, Certification, Information security, Geolocation.
Abstract:
In digital world, photography lost its legal value due to the massive usage and the ease of modifications. This
paper presents a watermarking technique which adds a proof of validity to a smartphone-captured photog-
raphy. By analysing the context of provability issues (attacks, impacts and objectives), the authors derives
requirements. The constraints of the domain leads to the specification of a semi-fragile algorithm, which
embeds pieces of information like geolocation or timestamp to insure the provability. An evaluation of the
process shows the cryptographic robustness of the algorithm.
1 INTRODUCTION
The development of smartphones and the all-
surrounding communication networks have modified
the handheld’s usages. Besides, society-driven inter-
ests, e.g. sustainable development, lead to paperless
office work. In that environment it is more convenient
for company to provide their employees with multi-
ple functions devices, which enables them to collect
and report field information. Mass market users have
contributed to the migration, as an example, by us-
ing their devices as electronic wallets. To summarise,
handheld devices profits their communication capa-
bilities to send and receive information. But with the
lack of information support, there is a problem to take
care of: the proof strength of the evidence. With ana-
logue photography, it is fair to consider the shot of
the clock tower timestamped and geolocalised. But
in the digital world, this obviousness is unclear. Be-
cause of the ease of digital manipulations, the proof
value of digital evidences becomes none. This ar-
ticle will present a digital-photography cetification-
dedicated method for handheld-devices snapshots.
Three constraints have to be met:
Process has to be cryptographically safe;
Process has to be adapted to device capabilities;
image must still be usable, with not too much
degradation.
It must be raised, that confidentiality is not tar-
geted. The owner must retain viewing capacity, but
the copy have to be considered as original. This
makes distinction between the presented watermark-
ing and copy-control system or digital right manage-
ment.
This article will firstly present a state of the art of
watermarking techniques. This part will remind some
required definitions and properties, show an overview
of security in watermarking techniques and present a
context specific attack model. In a second part, we
will describe a way to produce certified documents
from digital picture taken from mobile equipment.
This includes describing the mark, stating specifica-
tions and algorithm principles. Finally we will show
the result provided by such an algorithm, in terms of
security, invisibility, forgeries detection and time of
execution.
2 WATERMARKING STATE
OF THE ART
2.1 Definitions
As far as certification is concerned, watermarking
527
Stadler Y., Lanuel Y., Nagih A. and Herrmann F..
CERTIFICATION WATERMARKING FOR DIGITAL HANDHELD-CAPTURED PHOTOGRAPHY.
DOI: 10.5220/0003411305270534
In Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems (LOCSUE-2011), pages
527-534
ISBN: 978-989-8425-48-5
Copyright
c
2011 SCITEPRESS (Science and Technology Publications, Lda.)
comes as an essential tool. But there are many kinds
of watermarking techniques. As an illustration, in
(Furon, 2002), the watermarking is highly bound to
the signal processing and is tailored to protect the
copy rights, thus the robustness is assumed. In this
article, the watermarking definition will be based on
the works of Cox et al. (Cox et al., 2008): ”water-
marking [is] the practice of imperceptibly altering a
Work to embed a message about that work” where the
work is ”a specific song, video or picture or to a
specific copy of such”.
Mark detection or extraction process depends of
the targeted watermarking-characteristics. If original
work is required in such process, it is called an in-
formed watermarking, else it is a blind watermark-
ing (Kundur and Hatzinakos, 1999; Eggers and Girod,
2001).
Every watermarking modify the work (or host).
However, the host has different formats (equivalent
in term of information, but different presentation). As
far as image is concerned, two major insertion do-
main can be considered. The spatial domain – like a
bitmap is a traditional visual representation, a.k.a.
raw format. It is a three dimensional array in which
the first two dimensions are position information, and
the last is colour information. The most famous wa-
termarking using this domain is the Mintzer-Yeung al-
gorithm (Mintzer and Yeung, 1997) which has been
further analysed by Fridrich et al. in (Fridrich et al.,
2002). The second domain is called frequential do-
main. Many transform are used to convert a spatial
representation to a frequential one. Interest of such
techniques is to benefit the frequencies periodicity for
compression purpose. As an example Lin and Chang
use this domain to embed a mark in (Lin and Chang,
2000). For other algorithm using wavelets, readers
can refer to (Kundur and Hatzinakos, 1999).
2.2 Properties
The principal property of a watermarking algorithm
is robustness (Atupelage and Harada, 2008; Cayre
et al., 2005; Furon, 2005; Lin et al., 2000; zgr Ekici
et al., 2004; Rey and Dugelay, 2000). A watermark
is called robust when it achieves a high degree of ro-
bustness, meaning that modifications do not erase the
mark (thought they can degrade it). An example can
be found in (Rey and Dugelay, 2000), where robust-
ness is use to distinguish malicious manipulations of
images. On the contrary a fragile watermark has the
lowest robustness, as the watermark disappear with
the slightest modification. That process is used by
Wong (Wong, 1998) to verify authentication and in-
tegrity of a digital image. In between stands the semi-
PSNR = 10 · log
10
d
2
EQM
(1)
EQM =
1
mn
m1
i=0
n1
j=0
||I
o
(i, j) I
r
(i, j)||
2
(2)
Figure 1: I
o
original image, I
r
watermarked image.
fragile watermark, which is robust to a finite set of
modifications and fragile to all others. Exempli gra-
tia (Lin and Chang, 2000), authors proposed a water-
marking technique which is robust to JPEG compres-
sion.
Watermarking an image consist in embedding new
information into host, id est by modifying the host it-
self. Speaking of digital imagery, imperceptibility, as
original quality preservation, is required (Fei et al.,
2006; Kundur and Hatzinakos, 1999; Lin et al., 2000;
Fridrich, 1998). It can be stated that watermark im-
perceptibility has to meaning: human eye impercepti-
bility and computer imperceptibility. In both case, the
actor must be unable to distinct original image from
watermarked image. A way to measure the impercep-
tibility is PSNR (Peak Signal-to-Noise Ratio - see 1
and (Petitcolas. and Anderson, 1999)). In signal pro-
cessing community, it is admitted than 38dB is a good
PSNR. As an example, the watermarking algorithm
of Kundur and Hatzinakos (Kundur and Hatzinakos,
1999) provide a ratio of 43dB. Insertion rate is the
amount of information which can be stored in an im-
age watermark. It is also called capacity. In copy
control scenario, the capacity may be low. On the
contrary it must be high for indexation cases. Tech-
nics like matrix embedding proposed in (Fridrich and
Soukal, 2006) are used to increase the capacity of a
watermarking algorithm without increasing the image
degradation. For embedded application (such as mo-
bile equipment, video surveillance, etc), algorithms
have to be adequate with the mobiles capabilities, and
specifically for real-time applications. Complexity is
the indicator that will measure the watermarking pro-
cess fit (Atupelage and Harada, 2008; Fei et al., 2006;
Fridrich, 1998). An analogy can be made with paper
copies, within the process the screen imperfections
can induce anomalies, but the legal value remains the
same. This notion can be transferred to watermarking
algorithms by the notion of localisation. The princi-
ple is to include integrity checking into the process
(Atupelage and Harada, 2008; Lin et al., 2000). De-
tection can reveal defective areas and genuine areas.
2.3 Watermarking Algorithm’s Security
As we can see by the non-exhaustive enumeration of
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properties given in the previous subsection, most pro-
posed watermarking-algorithms offer different tun-
able parameters. Before giving specifications, the
context must be described.
2.3.1 CODASYSTEM’s Context
CODASYSTEM sells certification software based on
a secured infrastructure for digital handheld-captured
media. With the photographies, CODASYSTEMs ob-
jective is making digital proof. The deployed solution
is based on watermarking techniques which certifies
the location, time and issuer information.
In this context, being able to visualise image with-
out constraint is a requirement.
The certification process is divided in three sub-
activities:
Capture phase: meta-data are gathered and in-
serted by watermarking in the image.
Transmission phase: data are encrypted and sent
via a network to storage.
Storage phage: data are conserved for long term
support and available to user.
The ”certification chain” of CODASYSTEM is de-
scribed by figure 2.
User
Identification
(Password)
Multimedia
Capture
Authentication
(By
watermarking)
Secured
Transmission
GPRS/EDGE
Geolocation, timestamp, identification, ...
I. II.
II. III.
I. Capture / II. Transmission / III. Stockage
Watermarking
Encryption
Secure
storage
Figure 2: CODASYSTEMs certification chain.
However, all these properties does not provide cer-
tification by using only watermarking. Cryptographic
tools have to be used to protect meta-data. In fact,
as it has been said by Cox et al. ”Watermarking is
not cryptography” (Cox et al., 2006). This is the pro-
tocol which involves the watermarking and provides
the necessary cryptographic quality. To understand
these needs, possible attacks on certified images will
be presented.
2.3.2 Watermarking Attacks Classification
The literature provides many classifications (see as
an example (Kutter et al., 2000)). Most of the pre-
sented attacks are grouped by strategies (geometric
attacks, noising, etc.). These classifications are in-
teresting so as to get a global overview. But, depend-
ing on context, information to embed, or to protect,
varies much. Knowing the impact and the potential
benefits of the attack are important to orient the pro-
tection effort. This paper propose a contextual clas-
sification ordered by risk family. It has to be remind
that the current context is proof by image. A digital
photography is captured by a device and embed infor-
mation about author, geolocation, time and integrity.
All attacks presented here have a common point: in-
tegrity of image. An attack which leads to integrity
loss, fails.
Proof
Lost
False
Unauthorised
Reading
Attacks
Alibi Theft
Forgery
- Proof theft
Non relevant
Relevant
- Original proof replace
by another
- New proof creation
Alice's responsibility
Figure 3: Attacks classification.
On figure 3, the first level describes three fami-
lies of risk. Firstly, an attacker can choose to destroy
(erase) embedded information. In this case, he ob-
tains an non certified image (that is not exactly the
same as the original since the watermarking algorithm
is non reversible). This attack is not relevant because
even if the attacker owns a copy with no certification,
the original owner keeps possessing the original and
certified photography. In the case of removing the
mark from the original document, the problem does
not concern the watermarking technique, but the se-
cure storage. This is a strong issue, but is not in the
scope of this document. Secondly, the unauthorized
access to the mark is not wished, but this aspect is not
a strong constraint. If the attacker succeed to read the
embedded information such as geolocation or times-
tamp, nevertheless the image remains certified. These
attacks do not belong to the scope of watermarking
certification and many cryptography techniques can
handle this problem very efficiently. Lastly, the false
creation is very relevant and is the critical concern. If
such a false certified document would be forged, the
validity of the system is compromised. This family
can be divided in three sub-objectives: alibi, forgery
and theft.
To explain all cases of false and conflicts that can
occur, some definitions are required.
CERTIFICATION WATERMARKING FOR DIGITAL HANDHELD-CAPTURED PHOTOGRAPHY
529
T S is the TimeStamp function. It has an order
relation for its values. For all images x and y, if
x has been taken before y, then T S(x) T S(Y ) is
true.
Geo is the function of geolocation. It has an
equivalence relation. For all images x and y cap-
tured at the same exact place, Geo(x) = Geo(y).
Auth is the authentication function. If the image x
belongs to user y then Auth(x,y) is true.
The theft is defined by the production of a certi-
fied document with the intention of appropriating the
image of the original author. In other words, a theft
consist in putting the signature of the attacker instead
of the signature of the original author. For example,
Alice makes a photography of an event and certifies
it for owning a valuable proof. Oscar who was not at
that place, copies this photography and signs it with
it’s own signature. It is obvious that this new certified
photography does not retain Alice’s signature. Both
owns a certified document. But, to succeed, Oscar
must follow these steps:
Copy the original.
Erase Alice’s signature (formula 3)
Put his own signature (formula 4)
Make the timestamp is previous than the original
(formula 5)
That can be formalised by:
Auth(Image
Oscar
,Alice) = Faux (3)
Auth(Image
Oscar
,Oscar) = V rai (4)
T S(Image
Alice
) > T S(Image
Oscar
)(5)
Avoiding this kind of attack requires to protect
two aspects: author authentication and timestamp of
the capture. It is mostly the last point that requires
the most attention in the certification process. Many
works have already been focused on this issues, and
have led to reliable protocols. In the certification pro-
cess, we propose the use of a trusted third party which
guaranties and conserves the authenticated document.
Creating an alibi consists in the forging of a false
that belongs to the legitimate owner, but translated in
time (to prove one’s presence at a given place) or in
space (to prove that something happened at a given
time).
To build such a proof, Alice must at first create a
mark at her name with a chosen original. Eventually,
she can certified it with other information (formula 6).
This condition is common to all type of alibi.
Auth(Image
Alice
,Alice) = True (6)
Secondly, Alice should modify the timestamp or the
geolocation (formula 7 or 8 ).
T S(Image
Alice
) 6= T S(Alibi) (7)
Geo(Image
Alice
) 6= Geo(Alibi) (8)
As it has been evoked previously, reliable technical
solutions are available to guaranty the authenticity
and the timestamping. However, the geolocation re-
mains unreliable nowadays. Jamming, spoofing and
meaconning are relatively easy to set up. This will be
described below.
Forgery consists in certifying a document with the
identity of the victim. To implement this attack, Oscar
must build a mark with the Alice’s identity, and with
a photo that she has not captured (formula 9).
Auth(Image
Oscar
,Alice) = True (9)
In this attack, the authentication system is the essen-
tial point to protect. The certification protocol shall
not leak any information about the elements that has
permit to Alice to authenticate her images. Current
signature systems provide such a security.
To conclude, avoiding attacks presented above,
one shall meet some requirements : embedding in-
formation as close as possible of the capture process,
impossibility of forging a timestamp, impossibility
of changing geolocation data, impossibility of imper-
sonation. These security assessments lead to specify
the certification algorithm, described in the following
section.
3 CERTIFICATION
WATERMARKING
As it has been described previously, the certification
process is a sequence of operations which produces
an image that leaves no doubt about geolocation, au-
thor and time. The image is considered an original
and is stored in a trusted third party digital vault. In
other words, information are embedded in such a way
that making duplicates is easy and making fakes is
difficult. This section presents the structure of the
mark, describes more in detail the data capture, then
the properties of the watermarking certification will
be discussed. At last, technical aspects will be treated.
3.1 Mark for Certification
The host is both the asset to certify and the means to
transport the evidence itself. Thus, this mark is com-
posed of the bytes corresponding to the identity of the
author, the authenticated timestamp and the geoloca-
tion. This set of data, so-called meta-data, represent a
payload of almost 500 bytes.
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530
However, the watermarking algorithm must en-
sure the host integrity. The goal is not to prevent copy,
or the author identification, but to guaranty the con-
formity to original. Different works have covered the
granularity of the integrity control. The lowest level
consists in detecting any modification. At a higher
level, it is possible to localise what has been modi-
fied. For this type of watermarking algorithm, Guille-
mot (Guillemot, 2004) compares the mark with a spy
which will testify about the modifications that may
have been made. The pattern is a set of information
computed from the image, and are also inserted.
Meta-data are composed of critical information
for the proof. This information must of course be re-
liable to ensure the legal value. As it has been dis-
cussed, securing the timestamp information is rela-
tively easy. But, it is more complicated for geoloca-
tion. Technically, geolocation is computed from the
signal of, at least, three GPS satellites (four without
approximation). But these signals are weak and can
be distorted easily, naturally or voluntarily. This be-
comes of critical interest because such jamming or
meaconning devices can be obtain at a reasonable
cost. The ongoing FP7 project ATLAS ((Roberts
et al., 2010)) target the enhancement of geolocation
reliability during image capture. It is declined in sev-
eral scenarios:
Indication of current Quality of service (QoS).
Position enhancement and correction.
Device integrity monitoring.
Dedicated receiver.
The QoS indicator and the position enhancement
are based on referenced ground stations, that will be
compatible with Galileo system. Those services pro-
vide the user with the reception quality at its location,
indicating him if he is being attacked or not. The in-
tegrity monitoring is used to testify that the signal re-
ceived by the device has not been tampered with. It
uses constant monitoring of GPS signal and other cap-
tors (GSM, WiFi, etc.). Finally, the external receiver
can be used to gather more accurate signals than one
provided by the phone.
3.2 Algorithm Specifications
Some properties appear to be critical to certification
watermarking in the CODASYSTEMcontext. At first,
imperceptibility is essential to provide user with im-
ages not degraded by the mark. As the amount of
information to embed is important, the capacity must
also be important. A trade-off between those two op-
posite properties is necessary.
A non-author user shall produce a copy of any
proof he consult. This implies that a simple screen
shot of a certified image shall retain the certification.
Knowing that such an operation can lead to compres-
sion defects, the localisation properties is required for
being able to distinguish a certified copy from a tam-
pered photography. This cannot be achieve by a tradi-
tional signature process because of its fragility to all
modification. The certification watermarking can be
seen as a signature process. This signature must not
resist to any modifications. However, since we want
to allow to copy and to re-compress, the watermark
should resists to this modification. So the algorithm
has to be semi-fragile. As the re-compression may
raise small errors (rounding of floats), the algorithm
should make localisation possible, to distinguish ma-
licious and non malicious errors. In other word, all
the process must be integrated within the compression
phase. The context imposes us to use JPEG format.
So, the algorithm is based on this standard.
Then, the algorithm must provide security prop-
erties to resist the described attacks. So as to ensure
this, geolocation and timestamp information are im-
ported from reliable sources (Timestamping authority,
ATLAS). The author owns a certificate with its private
key to encrypt meta-data. The public key infrastruc-
ture for managing these certificates, is important to
the system, but not in the scope of this paper.
3.3 Algorithm Principle
We remind that JPEG compression process 8x8 pixels
blocks. After some stage of the compression process,
these blocks are converted to a 8x8 Discrete Cosine
Transform quantised coefficients block (DCT quan-
tised block). The first of these coefficients is called
DC and is never used for embedding (it would de-
grade the image too much). The others are the AC
coefficients whose Least Significant Bits (LSBs) will
embed the mark. The watermarking is made in such a
way to minimise the impact on image quality.
The algorithm is divided in three stages.
Stage 1: Selection and Exclusion. This is a deci-
sion stage that will assign a block to integrity or mes-
sage data. There are three cases: a block contains
integrity information (pattern), contains meta-data or
it does not meet the constraints that guaranty the in-
visibility of the embed. The tuning of this parameter
is based on the following statement: when a block is
homogeneous, it is composed of massive number of
zero coefficients because he has low spatial variation.
Those areas are not fit for watermarking since it will
be too visible. In addition, watermarking this kind of
CERTIFICATION WATERMARKING FOR DIGITAL HANDHELD-CAPTURED PHOTOGRAPHY
531
block may leak information, leading to security flaw.
This lead to the definition of the threshold notion in
function of the number of zero in the quantised DCT
block.
In this phase, the meta-data are divided in five bits
chunks. Each chunk will be included in one block.
All blocks not used for meta-data are used for the pat-
tern. The selection of which information will be em-
bedded in a block, is derived from the author’s key.
It is impossible to determine the type of embedding
without that key.
Stage 2: Pattern Computation. The pattern of a
block is a datum which reflects the visual content of
a block. It is comparable to a hash, traditional cryp-
tographic technique which provides integrity check.
To embed a chunk of ve bits (meta-data or pattern),
the 31 first ACs of the block are considered. With the
first five Most Significant Bits (MSBs) of each coef-
ficients, a five bit parity number is computed. Com-
bined with the datum to embed and the user key, it
produces a cryptic information for embedding that
is (approximately) similar to hashing functions. The
cryptographic results are sufficient and the computa-
tion is fast. Furthermore, adding the authentication
data makes it similar to HMAC digests. Each block
embeds its own five bits pattern.
Stage 3: Insertion. The principle consists in mod-
ifying some bits within the 31 LSBs previously se-
lected. The matrix embedding technique provides an
extremely simple and non destructive method to em-
bed five bits by modifying only one bit of those 31
LSBs.
4 EXPERIMENTAL RESULTS
4.1 Security Assessment
To evaluate the cryptographic robustness of the algo-
rithm, it is necessary to determined the information
known by the attacker. He knows the threshold value
for the selection. He also knows that only one bit
is modified to encode the five bits message. He has
access to a decoder which takes an image and a key
as parameters. This checker tells him true if all the
blocks of the image are integrated with the provided
key. In case of failure, he does not have the localisa-
tion of 3defective blocks.
In case of a theft, Oscar suppress Alice’s authenti-
cation and watermark his own authentication informa-
tion. To succeed he needs to embed an earlier times-
Table 1: PSNR measurements.
Nom Desk Babouin F16 Poivron
PSNR (en dB) 48.88 48.77 48.89 48.79
tamping information.
In case of an alibi, Alice herself needs to deter-
minate the repartition of pattern and meta-data blocks
within her images. Once again she has to tamper with
meta-data that come from trusted sources.
In both of those cases, each author embeds with
it’s own keys. Therefore the attacks are only of lit-
tle difficulty and that is why the meta-data security
is critical. The last case, forgery, is different. Os-
car wants to assign to Alice a proof. It is supposed
that Oscar has access to certified photography of Al-
ice. To identify the key, he needs to call the decoder
with a random key. The conditions of this attack are
analogue to a collision search for an hash function.
The key length must be sufficient to ensure a reason-
able probability of collisions and deter from taking
brute-force guess. If l is the key length, the birthday
paradox (Wagner, 2002) indicates that 2
l/2
tries are
enough to have a p = 1/2 chance of having collision,
i.e. guessing the right key. Nowadays, it is admitted
than a l 256 is sufficient.
4.1.1 Invisibility
References images (cited below) have been used to
estimate the quality performance in term of invisibil-
ity.
Baboon
F16
Pepper
mobile taken photography
Quality compression parameters are Q=92 for the
mobile device (fixed by the device) and Q=90 for the
reference images. This rate of compression is a fine
tuning to avoid compression artefacts. It will there-
fore be more easy to assess the watermarking defects.
The table 1 (formula 1) presents the results.
Average PSNR is 48.83dB which is very good for
watermarking algorithm.
4.2 Integrity Check
The tests have been performed with the following pro-
tocol.
Watermark the image
Modify the image by logo insertion
Mark extraction
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Figure 4: Modified image (a logo has been embedded).
Figure 5: Integrity default (the logo has been detected).
The results (Figure 5) show that defaults in in-
tegrity check are detected where the logo has been
included. It can be seen that some blocks appears to
be defective. They are re encoding errors due to the
rounding process in the JPEG compression.
4.3 False Key Checking
In this scenario, an image is decoded with a false au-
thor key (Figure 6 ). 96.95% of watermarked blocks
are considered corrupted. These observations prove
the efficiency of falsifications. This analysis, with lo-
cal information of tampered blocs, is unavailable to
the attacker, but for a forensics purpose (legal action
for example) localisation is obviously important. The
judge has the final word on whether he accepts or not
the photography as a proof based on the number of
unimpaired blocks.
1
4.4 Execution Time
The table 2 presents the execution times of the al-
gorithm on an ASUS P535 phone (specifications are
available on the manufacturer website). The F5 al-
gorithm is described in (Westfeld, 2001) and has
been enhanced to fit mobility needs. The results
1
This observation is based on French laws.
Figure 6: False key decoding.
Table 2: Execution times.
Mobile: ASUS
F5 Certification watermarking
Total incl. JPEG incl. Tatouage
3.864 0.800 0.300 0.500
has been obtained on 640x480 photography without
sub-sampling. The algorithm that has been devel-
oped, shows improvement of ve times compare to
F5. Considering the time used for JPEG compres-
sion, the watermarking process time is compatible
with handheld devices.
5 CONCLUSIONS
The evolution of mobile devices, in terms of technolo-
gies and software, has generated a change of usages
in the status of broadcast information. This article
has presented an algorithm which provides security
to digital capture, in order to use them as proofs. The
experiments had proven the good usability and fit of
the process. A risk assessment has also been pre-
sented to justify the different features that has been
selected in the specification process. This algorithm
is semi-fragile and provides localisation of tampered
areas. The security of the technique is based on the
algorithm capacity of preserving integrity and the re-
liability of meta-data gathering.
Some future works can be foreseen. The first
point is related to GNSS. These problems, stated in
this article, are the major subject of the ongoing FP7
project ATLAS. A second perspective is the portage
of such an algorithm to video. In fact, many standards
are based on the same elements such as H.264 and
MPEG, which use the Discrete Cosine Transform al-
most the same way as JPEG does. Nevertheless there
would be new problematics, that is to say intra/inter
predictions and flow control as an example. To finish
with, the algorithm itself may benefits some improve-
CERTIFICATION WATERMARKING FOR DIGITAL HANDHELD-CAPTURED PHOTOGRAPHY
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ments. A good feature to be added would be the abil-
ity to use a wider range of recompression parameters
within JPEG process without mark loss.
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