## 3 Results  
In this section, the performance of the proposed system is analyzed for twenty-three test cases. These images belong to twenty male participants and three females. Figure 11: Stage 5 Vein Selection using Model B for image with oneevel downsample: (**a**) Highlighting Vein for Binary Image; (**b**) Detected Vein in the Cropped Image. Figure 12: Stage 5, vein selection using Model B for image with twoevels downsample: (**a**) highlighting vein for binary image; (**b**) detected vein in the cropped image. The redine and greenine in Figures (**a**,**b**) correspond to the vein extraction’s output that is displayed through the segmented and captured images respectively. The following figures illustrate the proposed vein extraction module by presenting the results from the vein selection stage using Models A and B separately on a set of test cases images. There are six groups of vein selection results. Comparing both Model A and Model B, the selected vein is either identical, similar, or different. Group A refers to the vein selection results when vein selection is identical when deploying Model A or Model B. Group A has about 21.74% of the test cases. Figures 13 and 14 show the identical vein selection from both models. In all figures,abels Model B0, Model B1, and Model B2 refer to Model B results when operating on original image resolution, onevel of downsample and twoevels of downsample, respectively. Group B is related to the vein selection results when both Models A and B obtain similar vein selection. Group B contributes about 26.1% of the test cases. Part of this group's cases are depicted in Figures 15 and 16. Figure 16: _Cont._  
Figure 14: Matching vein selection results for Image 12: (**a**) original image; (**b**) models’ output. Figure 15: Similar vein selection results for Image 16: (**a**) original image; (**b**) models’ output. In Group C, Model and Model B extract different vein selections, and both results are accepted for the vein injection. This group has about 8.7% among all test cases. Parts of these results are depicted in Figures 17 and 18. Groups D and E refer to images when one of the models (A or B) succeeds in retrieving the correct vein while the other model fails. Group D relates to the success of Model A to detect the correct vein while Group E corresponds to the correct vein selection from deploying Model B only. Both models have about 34.8% of test cases. Figures 19 and 20 represent results related to Group D, while Figure 21 shows an example of Group E's results. The amounts of cases related to Groups D and E are 30.43% and 4.35%, respectively. Considering Group D's results in more detail, it is important to note that in all the case tests where Model A successfully extracts the correct vein for injection, Model B has several selections. Although one of these vein selections is similar to the corresponding one identified by Model A, it is not suggested during the vein extraction module. This is because of the unconformity for theine validation condition that occurs when deploying Model B. When there is noine coincident among theines extracted from deploying Model B, no vein is detected for the vein injection. Figure 16: Similar vein selection results for Image 22: (**a**) original image; (**b**) models’ output. Figure 17: Multiple correct vein selections for Image 1: (**a**) original image; (**b**) models’ output. Figure 19: Model A correctly identifies vein selection for Image 6: (**a**) original image; (**b**) models’ output. Figure 18: Multiple correct vein selections for Image 15: (**a**) original image; (**b**) models’ output. Figure 21: Model B correctly identifies vein selection for Image 3: (**a**) original image; (**b**) models’ output. Figure 12:0 Model A correctly identifies vein selection for Image 9: (**a**) original image; (**b**) models’ output. Theast category (Group F) represents test results that indicate false vein selection from both models. This group has about 8.7%, corresponds to two test images.