## 4 Experimental Results  
To evaluate the performance of the proposed ARDHA technique, experiments were carried out using Lena, blackb, Portofino, and ship, which were 512 images \(\times\) 512 images shown in Figure 13, as cover images. The abstract in this paper was converted to ASCII code and used as confidential data. In the experiments, the confidential data were embedded in the cover image using proposed and existing techniques. The image generated by embedding confidential data in the cover image is called a stego-image. Figure 13: _Cont._The values of the variables used in this paper were as follows: the alpha (\(\alpha\)) used in Equations (9) to (10) was set to 0.45. In general, local similarity exists in images. Therefore, the closer the pixels are, the more similar the pixel values. To reflect this characteristic, when calculating the predicted value V\({}_{1}\) using Equation (9), the weight of the adjacent pixels affecting the calculation of V\({}_{1}\) was set to 1. The \(\alpha\) is the weight that pixels, which are one pixel apart, contribute to the V\({}_{1}\) calculation. To reflect local similarity, we set \(\alpha\) to 0.45, which is much smaller than 1. The experiment was carried out while changing the threshold (\(\beta\)), which is used in Step 1.4 to 1.5, from 0 to 20. The reference value (\(\epsilon\)) used in Step 1.7 was set to 10. The dev2 obtained by Equation (17) is the sum of the absolute values of the differences between the avg and the neighboring pixels. If dev2 is much larger than the avg, it is very unlikely that it will be a simple concave surface or a simple convex surface because the change in pixel values around the location is large. For this reason, \(\epsilon\) was set to 10; thus, the deviation between the avg and each pixel is less than 1 on average. The K used in Equation (26) was set to 4. In the cases of simple convex and simple concave surfaces, the pixel values change gently. Therefore, the average value can be used to more accurately predict the pixel values in a simple convex surface or a simple concave surface. K was set to 4 to reflect the avg with the same weight as \(\text{con}[\text{x}_{1}]\), \(\text{con}[\text{x}_{1}]\), \(\text{con}2[\text{x}_{1}]\), and \(\text{con}3[\text{x}_{1}]\). When predicting pixel values using edge characteristics, strong_edge was set to 1, normal_edge was set to 0.75, weak_edge was set to 0.5, very_weak_edge was set to 0.25, and non-edge was set to 0 in Equation (35). Specific values were set owing to the following reason: The stronger the edge characteristic, the more it should be reflected in the pixel value prediction. Therefore, by setting strong_edge to 1, strong_edge has the greatest influence on the pixel value prediction. By setting no_edge to 0, no_edge has no influence on the pixel value prediction. The normal_edge and weak_edge have values evenly distributed between 1 and 0. The difference threshold (\(\delta\)) used in Equation (37) was set to 1.6. To satisfy local similarity, the predicted value V\({}_{4X}\) must have a value close to V\({}_{2}\). Therefore, the \(\delta\) should be set to a small value. The R\({}_{\text{S}}\), R\({}_{\text{N}}\), and R\({}_{\text{W}}\) used in Equations (36), (38), and (39) are 1.1, 0.9, and 0.7, respectively. R\({}_{\text{S}}\) was determined based on the average of all edge values at all locations with one or more strong edges. R\({}_{\text{N}}\) was determined based on the average of all edge values at all locations with no strong edges and at  
Figure 13: Cover images and stego-images. least one normal edge. R\({}_{\rm W}\) was determined based on the average of all edge values at all locations with no strong or normal edges, and with at least one weak edge. Lena, blackb, Portofino, and ship images used as cover images are shown in Figure 13a.1-d.1. The stego-images, which are the experimental result images generated by embedding confidential data in cover images using the APD, APDLS, and ARDHA techniques, are shown in Figure 13a.2-a.11,b.2-b.11,c.2-c.11,d.2-d.11.