2014 RISP International Workshop on Nonlinear Circuits,Communications and Signal Processing
NCSP'14, Honolulu, Hawaii, USA. February 28 - March 3, 2014

Extraction of Intermediate Brightness by CNN Using Two Kinds of Cloning Templates
Yoshio Nakayama1 , Yasuteru Hosokawa1 , Yoshifumi Nishio2 and Naomi Suzuki1
1Shikoku University
Furukawa, Ohjin, Tokushima, Japan
Phone: +81-88-665-1300
FAX: +81-88-637-1318
E-mail: ny.h.s.t.g@gmail.com
E-mail: hosokawa@keiei.shikoku-u.ac.jp
E-mail: isoda@keiei.shikoku-u.ac.jp

Abstract
In this study, a cloning template for CNN using Two kindsof cloning templates is introduced. The template can extract
intermediate brightness parts of an images. A similar processing by a conventional CNN is also introduced. By comparing
the two results, the advantage of CNN using Two kinds ofcloning templates are shown.

2Tokushima University
2-1 Minami-Josanjima, Tokushima, Japan
Phone: +81-88-665-7470
FAX: +81-88-665-7471
E-mail: nishio@ee.tokushima-u.ac.jp

study. This system has two kinds of cloning templates. Cells
having one template set are called as Cell α and the otherare called as Cell β. These two cells are placed as checkeredpatterns.
The state equations of the cells are given as follows:
1: The case that i + j is an even number.
dxij= − xij + Iα
dt∑+Aα (i, j; k, l)ykl

1. Introduction

c(k,l)

Many modified Cellular Neural Networks [1]-[10](CNNs)
have been proposed. Most of modified CNN obtained higher
ability in exchange for losing the simplicity of the system.
However, the simplicity is important characteristics of CNNs.
CNN using two kinds of cloning templates was proposedby Fujii et al [6]. The feature of this modified CNN is not lostthe simplicity. Some interesting phenomena which are active
pattern formations, clustering and so on are observed. The
system was investigated as coupled oscillatory system mainly.
Therefore, the applications is not investigated. In order toexpand the potentialities, investigating its applications is an
important task.
In our previous study, new cloning template of CNN using
two kinds of cloning templates is proposed in [10]. The template can extract the intermediate brightness parts of an image
with one process.
In this study, CNN using two kinds of cloning templates
are compared with a conventional CNN by processing the extraction of the intermediate brightness parts.

+∑

(1)

Bα (i, j; k, l)ukl

c(k,l)

2: The case that i + j is an odd number.
xij= − xij + Iβdt∑+
Aβ (i, j; k, l)ykl
c(k,l)+∑(2)Bβ (i, j; k, l)ukl

c(k,l)

A{αβ} (i, j; k, l)ykl , B{αβ} (i, j; k, l)ukl and I{αβ} are calledas the feedback coefficient, the control coefficient and the bias
current, respectively.
The output equation of the cell is given as follows:yij = f (xij ).

(3)where,f (x) = 0.5(|x + 1| − |x − 1|).
(4)
The variables u and y are the input and output variables of
the cell, respectively. Aα , B α , Aβ and B β are 3 times 3
2. CNN using two kinds of cloning templates
matrices, which can be described to have a similar form toFigure 1 shows the CNN using two kinds of cloning tem- Eq. (5).
plates. The system has a two-dimensional M by N array Aα (i, j; i − 1, j − 1) Aα (i, j; i − 1, j) Aα (i, j; i − 1, j + 1)
structure. Each cell in the array is denoted as c(i, j), where  Aα (i, j; i, j − 1)
Aα (i, j; i, j)
Aα (i, j; i, j + 1) (i, j) is the position of the cell, where 1 ≤ i ≤ M andAα (i, j; i + 1, j − 1) Aα (i, j; i + 1, j1) Aα (i, j; i + 1, j + 1)
1 ≤ j ≤ N . The coupling radius is assumed to be one in this(5)-9-jic(i,j)(a) Original image.

(b) Result.

Figure 2: Computer simulation result of CNN using twokinds of cloning templates. Iα = 0.0 and Iβ = −5.0.
Cell αCell βFigure 1: Structure of CNN using two kinds of template sets.

3. Cloning templates for an extraction of intermediatebrightness

(a)

(b)

In this section, cloning templates for an extraction of interFigure 3: Computer simulation results of CNN using twomediate brightness are introduced.
kinds of cloning templates. (a) Iα = 3.0 and Iβ = −3.0,(b) Iα = 5.0 and Iβ = −5.0.
3.1 CNN using two kinds of cloning templates
By using following cloning template, intermediate brightness parts are extracted as checkered.

2 1 22 0 2
Aα = 0 2 0 , Aβ = 1 2 1
2 0 22 1 2
0 1 0−1 −1 −1(6)B α = 1 0 1 , B β = −1 2 −1 ,0 1 0−1 −1 −1Iα = 2 and Iβ = −2.

A cloning template of a binarization is shown as follows.

0 0 00 1 0
A = 1 2 1 , B = 0 0 0 and I = 0.2.
0 1 00 0 0(7)Figure 4 shows the computer simulation result. By changing parameter I, the threshold value can be changed.
A cloning template of a subtract two images is shown asfollows.

0 0 0000A = 0 1.5 0 , B = 0 −1.5 0
(8)
0 0 0000

The computer simulation results are shown in Fig. 2. Figure 2 (a), (b) shows the original image and the simulated result, respectively. Dark area and bright area become black andand I = −1.5.
white, respectively. The intermediate area becomes checkFigure 5 shows the computer simulation result. By subered pattern. Changing the parameters Iα and Iβ is corresponding to the brightness and sensitivity of the extracted area tracting Fig. 5 (b) from Fig. 5 (a) Fig. 5 (c) is obtained.
like as shown in Fig. 3. Peaks of border areas are observed
because boundary cells are set as black in this simulation.
4. Comparison
3.2 Conventional CNN
In order to extract of intermediate brightness, combining
two following cloning templates are needed.

In order to compare a CNN using two kinds of cloning templates and a conventional CNN, Computer simulations usingsame original image are carried out. Figure 6 shows the original image. Figure 7 shows a computer simulation result in- 10 -

CNN using two kinds of cloning templates and a conventional
CNN, an advantage of a CNN using two kinds of cloning templates is shown.
References(a) Original image.

[1] L. O. Chua and L. Yang, “Cellular Neural Networks:
Theory,” IEEE Trans. Circuits Syst., vol. 35, no. 10,pp. 1257–1272, 1988.

(b) Result.

[2] L. O. Chua and L. Yang, “Cellular Neural Networks: Applications,” IEEE Trans. Circuits Syst., vol. 35, no. 10,pp. 1273–1290, 1988.

Figure 4: Computer simulation result of a binarization.

[3] L. O. Chua, M. Hasler, G. S. Moschytz and J. Neirynck,“Autonomous Cellular Neural Networks: a unified
paradigm for pattern formation and active wave propagation,” IEEE Trans. Circuits Syst. I, vol. 42, no. 10,
pp. 559–577, 1995.

(a)[4] P. Arena, S. Baglio, L. Fortuna and G. Manganaro, “SelfOrganization in a Two-Layer CNN,” IEEE Trans. Circuits Syst. I, vol. 45, no. 2, pp. 157–162, 1998.

(b)[5] Z. Yang, Y. Nishio and A. Ushida, “Generation of Various
Types of Spatio-Temporal Phenomena in Two-Layer Cellular Neural Networks,” IEICE Trans. Funds., vol. E87A, no. 4, pp. 864–871, 2004.
[6] J. Fujii, Y. Hosokawa and Y. Nishio, “Wave Phenomena
in Cellular Neural Networks Using Two Kinds of Template Sets,” Proc. of NOLTA’07, pp. 23–26, 2007.
(c)[7] M. Oda, Z. Yang, Y. Nishio and A. Ushida, “Analysisof Two-Dimensional Conductive Plates Based on CNNs,”
Proc. of NCSP’05, pp. 447–450, 2005.

Figure 5: Computer simulation Result of subtraction. (a)Original image set as an input image. (b) Original image set [8] Z. Yang, Y. Nishio and A. Ushida, “Image Processing
as an initial state. (c) Result.
of Two-Layer CNNs — Applications and their Stability,”
IEICE Trans. Funds., vol. E85-A, no. 9, pp. 473–490,
2002.
the case of a CNN using two kinds of cloning templates. Thecloning template is set as Eq. (6) except parameters Iα and Iβ . [9] Z. Yang, K. Tsuruta, Y. Nishio and A. Ushida, “InvestiIntermediate brightness parts are extracted as checkered patgation of Phase-Wave Propagation Phenomena in Secondterns. Figure 8 shows a computer simulation result in the case
Order CNN Arrays,” Proc. of ISCAS’04, vol. 3, pp. 49–of a conventional CNN. Intermediate brightness parts are ex52, 2004.
tracted as black. Similar results are obtained. However, in thecase of the conventional CNN, some processing are needed [10] Y. Nakayama, Y. Hosokawa and Y. Nishio, “Possibility of Image Processing by CNN Using Two Kinds ofas shown in Fig. 9. Therefore, we can mention that a CNN
Cloning Templates,” Proc. of NCN’13,pp. 81–84, 2013.
using two kinds of cloning templates has a advantage in thispoint.
5. Conclusions
In this study, we have introduced cloning templates foran extraction of intermediate brightness. By comparing a- 11 -

Figure 6: Original image ( Woman ).

binarization(high)binarization(low)subtraction
Figure 7: Computer simulation result in the case of a CNN
using two kinds of cloning templates. Iα = 1.5 and Iβ =−1.9

Figure 9: Processing for the extraction of intermediate brightness by a conventional CNN.

Figure 8: Computer simulation result in the case of a conventional CNN.

- 12 -