平成 29 年度電気関係学会四国支部連合大会 講演論文集 (2017 愛媛大学)
2017 SHIKOKU-SECTION JOINT CONVENTION RECORD OF THE INSTITUTES OF ELECTRICAL AND RELATED ENGINEERS (EHIME)

1-8Cellular Neural Networks
with Using Two Templates in Combination
Takahisa Ando Yoko Uwate Yoshifumi Nishio(Tokushima University)

1. Introduction

3. Simulation Results

In the image processing of the Cellular Neural Networks(CNN), it is difficult to process complex parts of the input
image; edge, background, etc. Some researches are reported
that it is possible to process complex parts by switching twotemplates which have the different feature. Therefore, we
propose a new CNN method of using two templates by themaximum and the minimum output values of surrounding
the center cell. We apply the proposed method to somesimulations and investigate its performance.

In this section, we show a simulation result of noise removal processing by using the proposed method.

2. Proposed Method

(a)

(b)

The feature of the proposed method is using two templates by the maximum and the minimum output values(vymax : cell’s maximum output value, vymin : cell’s minimum output value) of surrounding the center cell. In
the proposed method, we define the center cell as the cellwhich is applied the template. The concept of the proposed
method is shown in Fig. 1.

(c)(d)
Figure 2: Simulation results. (a) Input image. (b) Simulation
result of the “Small object remover” template. (c) Simulation
result of the “Heat diffusion” template. (d)Simulation result of
the proposed method (n = 5).

Figure 2 shows the input image and the simulation results by the “Small object remover” template, the “ Heatdiffusion ” template and the proposed method. The input
image has many dots and graphics; circle, dogleg. In thissimulation result, we define many dots as noise of the input
image and 1st template is the “Small object remover” template and 2nd template is the “Heat diffusion” template. InFig. 2(b), by using the “Small object remover” template,
low dots are removed, however, general dots remain. On
the other hand, in Fig. 2(c), all dots are removed, however,graphics are processed indistinctly by using the “Heat diffusion” template. In Fig. 2(d), all dots are removed andgraphics are remain clearly. From the simulation results,
the proposed method removed noise of the input image byapplying the “Heat diffusion” template to the parts of dot.

Figure 1: Proposed CNN
The processing steps of the proposed method are described as follows.
Step 1: First, decide the center cell and the size of n×n
neighborhood. Then, find the vymax , and vymin from thatrange.
Step 2: Secondly, determine if the center cell has vymaxor vymin .

4. Conclusions
In this study, we have proposed a new method of using
two templates by the output values of neighboring cells.
The simulation results show that the proposed method iseffective to remove noise of the input image. Therefore, theproposed method is effective in noise removal processing. In
the future work, we will confirm that the proposed method
is effective for another image processing.

Step 3: Thirdly, the template is applied to the centercell. In case that the center cell has vymax or vymin , it isapplied 2nd template. In the other case, it is applied 1sttemplate.
Step 4: Finally, Step 1 to step 3 are applied to all cells
and repeated every 0.005 [τ ].

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