Journal of Robotics, Networking and Artificial Life, Vol. 3, No. 2 (September 2016), 107-110

An Authentication Method Using a Discrete Wavelet Transform for a Recaptured Video
Ren Fujii , Yasunari Yoshitomi, Taro Asada, and Masayoshi Tabuse

Graduate School of Life and Environmental Sciences, Kyoto Prefectural University,
1-5 Nakaragi-cho, Shimogamo, Sakyo-ku, Kyoto 606-8522, Japan
E-mail: { r_fujii, t_asada}@mei.kpu.ac.jp, {yoshitomi, tabuse}@kpu.ac.jp
http://www2.kpu.ac.jp/ningen/infsys/English_index.html

Abstract
Recently, several digital watermarking techniques have been proposed for protecting the copyright of moving
image files by hiding data in the frequency domain. In the present study, we applied our method for authenticating amoving image, which uses a discrete wavelet transform for a static image and a method for selecting several frames
from a moving image, to a recaptured video. In contrast to digital watermarking, no additional information isinserted into the original moving image by the proposed method.
Keywords: Authentication, Moving image, Copyright protection, Recaptured video, Wavelet transform

1. Introduction
Digital watermarking is a promising method forprotecting the copyright of digital data. Several studies
have developed methods in which a digital watermark(DW) can be extracted from data, even aftercompression, and the quality of the digital data remains
high after the DW has been embedded. However, there
is usually a tradeoff between these two properties. For a
useful DW, any distortion it introduces must be
imperceptible, and it must be robust to signal processing
methods, such as compression or attempts to delete it.
Both the processing rate and the complexity of DWs
have adversely affected their performance.
In order to overcome these performance issues, wedeveloped alternative authentication methods for digitalaudio1 and static images.2 These methods use a discrete
wavelet transform (DWT), and in contrast to digitalwatermarking, our method for static images2 does notinsert additional information into the original digital
data. The authentication is based on features extracted
by a DWT and a characteristic code.

In the present study, we will review our method3
for authenticating a digital moving image; it is acombination of our previously proposed method2 forstatic images and a proposed method3 for selecting
several frames from a moving image. As in our method2for static images, no additional information is inserted
into the original moving image, and it is authenticatedby features extracted by a DWT and a characteristiccode. We present the results of an experiment in which
we evaluated the ability of our proposed authentication
method3 to recapture a moving image. We will describe
this method3 and present the results of the experiment in
the following sections.
2. Observed Phenomenon Underpins theAuthentication Method
It has been observed that when a DWT is applied to anatural image, in the histogram of the wavelet
coefficients of the multi-resolution representation(MRR), the center of the distribution is very close tozero.4 We exploited this phenomenon in order to

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Ren Fujii, Yasunari Yoshitomi, Taro Asada, Masayoshi Tabusedevelop an authentication method for a static image.2
For further information on the DWT, see Refs. 5 and 6.
3. Authentication Ratio
We set the authentication parameters as discussed below.2
In Fig. 1, Th′(minus) was chosen so that it′ individes the nonpositive wavelet coefficients ( S mtotal frequency) into two equal groups, and Th ′(plus)
was chosen so that it divides the positive wavelet
coefficients ( S ′p in total frequency) into two equalgroups. Next, the values of the parameters T 1′ − T 4′ ,which control the authentication precision, were chosensuch that the following conditions were satisfied:1) T 1′ < Th′(minus) < T 2′ < 0 < T 3′ < Th′(plus) < T 4′ .
2) The value of S T′ 1 , the number of wavelet coefficientsin (T 1′, Th′(minus)) , is equal to ST′ 2 , the number ofwavelet coefficients in [Th′(minus), T 2′) , i.e., ST′ 1 = ST′ 2 .
3) The value of ST′ 3 , the number of wavelet coefficients

Fig. 1. Three sets (F, G, and H) of MRR wavelet coefficientsused for authentication.1

performance. Finally, this sequence of bi′ values is usedto form the authentication code C′.
The authentication ratio AR (%) is defined asfollows:in (T 3′, Th′(plus)] , is equal to ST′ 4 , the number ofwavelet coefficients in (Th′(plus), T 4′) , i.e., , ST′ 3 = ST′ 4 .

100AR =N

∑ f (1 − b − b′ )ii =14) ST′ 1 / S m′ = ST′ 3 / S ′p .

′In the present study, the value of both ST′ 1 / S mand ST′ 3 / S ′p is set to 0.25, which is the same settingused for creating the code for the original image file2.
When preparing the authentication codes, the wavelet
coefficients V ′ for each MRR sequence are divided
into three sets (hereinafter referred to as F, G, and H), as
shown in Fig. 1; these sets are defined as follows:• F = {V ′ | V ′ ∈ V ′ AC , V ′ < Th' (minus )}• G = {V ′ | V ′ ∈ V ′ AC , Th' (minus ) ≤ V ′ ≤ Th' ( plus )}• H = {V ′ | V ′ ∈ V ′ AC , Th' ( plus ) < V ′} ,AC

where V ′is the set of wavelet coefficients from thetarget image file that is used to create the authenticationcode.
The wavelet coefficients Vi′ are then classified
according to the following rules with the flags f i usedin creating the original code C:
When f i = 1 and Vi′∈ G , bi′ is set to 0.

When f i = 1 and Vi′∈ (F ∪ H ) , bi′ is set to 1.
When f i = 0 , bi′ is set to 0.5.

Note that the value 0.5 can be chosen arbitrarily, since
the value of bi that is the bit for creating the code forthe original image file2 does not influence the method'sN∑ii,(1)

fii =1

where N is the number of wavelet coefficients chosen
to create the authentication code for the original image
file.2 As can be seen in equation (1), neither bi nor bi′
influence the value of AR when f i = 0 , which occurs
when the corresponding Vi that is the wavelet
coefficient of the original image is not selected forcoding in the original image file.2
To use the proposed method, we need to store theflags f i and the original code C for each copyrighted
file that we want to protect. When calculating (1) inorder to authenticate an image file, we do not use theoriginal image file; instead, we use the flags f i and thecode C for that file.2

4. Authentication of a Moving Image
We applied our proposed authentication method3 to arecaptured digital moving image. We explain theproposed method3 in this section.
4.1. Authentication code
We obtained 10 codes for each moving image segment,each of which had.
Step 1: Let N total be the total number of frames in themoving image. Calculate frame No. k B , where k B is the

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An Authentication Method Usingsmallest integer not less than 0.1× N total , and calculate
frame No. k E , where k E is the largest integer not
greater than 0.9 × N total .
Step 2: Output the images of frames No. k B and k B+1
as BMP files. For each pixel, evaluate the difference
between the grayscale level in frame No. k B and that inframe No. k B+1 . Calculate the total sum S [1] ofsquares of these differences. Store the grayscale levelsof frame No. k B+1 in array A1 . Set the initialconditions as C[1] := k B + 1 , count := 1 , and k :=k B +2 .

Step 3: If k =k E +2 , go to Step 8. Otherwise, go to Step
4.
Step 4: Overwrite the image of frame No. k onto thatof frame No. k B −2 in the BMP file. Store the grayscalelevels of frame No. k in array B . For each pixel,evaluate the difference between the grayscale level inframe No. k − 1 and that in frame No. k . Calculate thetotal sum T of squares of these differences. Update thevalue of k to k := k + 1 .
Step 5: If count < 10 , update the value of count tocount := count + 1 , and go to Step 6. Otherwise, go toStep 7.
Step 6: Overwrite the array Acount with B, i.e.,
A count := B . Set S[count ] := T , and C[count ] := k − 1 .
Go to Step 4.
Step 7: Calculate l = arg max S [i ] . If S [l ] > T ,i =1, 2,,10

overwrite the array Al with B, i.e., A l := B . Set

S [l ] := T , and set C[l ] := k − 1 . If k =k E +1 , go to Step

8. Otherwise, go to Step 4.
Step 8: Output the arrays Ai (i = 1,2,  ,10) as BMP
files. Obtain the codes and flags used for theauthentication codes by using the method described inRef. 2. Output the codes, the flags, C[i ](i = 1,2,,10) ,and S [i ](i = 1,2,  ,10) .
4.2. Authentication

We used the method described in Section 4.1 to selectframes from moving images. The codes and the flags forthe selected frames were obtained using the methods
described in Ref. 2. For a given test moving image and agiven moving image in the database, the authentication
ratio of the test moving image to the moving image inthe database is defined as the largest authentication ratioof any selected frame in the test moving image to any
selected frame in the moving image in the database.
This is determined for each moving image in thedatabase, and the one with the highest authentication
ratio is selected as the assumed original image.
5. Experiment
We evaluated the performance of the proposed methodby conducting a computer experiment. In this section,
we present the results.
5.1. Method
The experiment was performed in the following
computational environment: Dell OptiPlex 3020; CPU:Intel Core i5-4570 3.2 GHz; 4.0 GB memory; OS:
Microsoft Windows 7 Professional. The development
language was Microsoft Visual C++ 6.0.
The experiment proceeded as follows. We obtained
77 moving image segments, provided as MPEG-1 files,
from MUS-CLE-VCD-2007.7 These were converted fromRGB components into YCrCb components, and for eachof these segments, we obtained ten codes for Ycomponents. We numbered the segments in the order inwhich they were recorded and then divided them into 11
groups of 7 members each. We then chose the sixsegments (Nos. 24, 45, 27, 21, 93, and 91) that recorded
the middle amount of time in each group that had theshortest to the sixth shortest recording time among 11
groups. Nos. 24 and 45 were monochrome, and so wereplaced them with the two segments that had the mostsimilar recording times, Nos. 100 and 34, respectively.
These six segments were displayed on a liquid crystal
television screen of Panasonic VIERA TH-19C305, andthe moving images were recaptured by a digital video
camera (Sony Handy-cam HDR-CX7); they were thensaved as MPEG-2 files, followed by cutting uselessmargin and being saved as MPEG-4 files. Divide allframes into 10 groups for each file by the time from thebeginning, and pick up 10 frames per a group by ourpreviously proposed method3 except the first and lastgroups in the sense of time from the beginning. This
resulted in 80 frames for each recaptured moving image,and these were used for authentication of the 77 segments.
We used FFmpeg8 to output a BMP file for eachsegment; 24 bits were used for the grayscale level andthe image consisted of 256 × 256 pixels. For the DWT,
we used Daubechies wavelets. Based on the results ofpreliminary experiments, we used the LH components
obtained from the DWT up to level 4.2

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Ren Fujii, Yasunari Yoshitomi, Taro Asada, Masayoshi Tabuse

Several consecutive frames in which most pixels
are black (or most are white) are sometimes inserted
into a moving image, because they can be useful for
scene transitions. A frame in such a series is neither
representative nor unique to that moving image, and if it
is selected to be coded, it could damage the ability of
the code to authenticate that moving image. Therefore,
we used only frames in which the average grayscalelevel for the Y component was in the range of 5 to 250(the full range is 0 to 255).
5.2. Results and discussion
Table 1 shows some examples of the authentication ratios
obtained in the experiment. In the six moving image
segments (Nos. 100, 34, 27, 21, 93, and 91), the averageauthentication ratio was in the range 71.6% to 74.3%
when the recaptured segment was from a different sectionof the original moving image, but it was in the range of
91.7% to 97.0% when the recaptured segment was fromthe same segment; see Table.1. When authenticating therecaptured segment No. 93 against the codes of theoriginal segment No. 17, the authentication ratio was90.1%. This unusually high authentication ratio wascaused by a pair of similar structures, which can be seenin the frames shown in Fig. 2. An example ofauthentication by the proposed method is shown in Fig. 3.
Table 1. Authentication ratios for recaptured moving images.
Original file No. for recaptured moving image
Average for others
For corresponding
raw file
Maximum forothers
Recording time
(min:sec)

100

34

27

2193

91

73.9

73.1

74.3

73.5

71.6

72.4

95.5

94.7

96.2

97.0

94.7

91.7

87.1

82.6

86.4

84.8

90.1

88.6

00:30

03:20

06:58

11:32

14:50

19:50
(%)

6. Conclusion
We applied our proposed authentication method3 to arecaptured digital moving image in order to evaluate theability of the method to recapture a moving image. In
contrast to digital watermarking, in the proposed
method, no additional information is inserted into theoriginal moving image. The experimental results showthat the proposed authentication method performs well.

Fig. 2. Left: recaptured frame of moving image segment No.
93; right: frame of moving image segment No. 17 in thedatabase.

Fig. 3. Left: recaptured frame of moving image segment No.
27; right: frame in the database with an authentication ratio of
96.2% with segment No. 27.

References
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Authentication method using a discrete wavelet transform
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