# SecureVision: An Open-Source User-Customizable Image Encryption Program
## 3 Results and Discussion
### Examples and Testing  
To extensively check the present program, we performed a number of tests using images with different sizes and resolutions. Five (5) example images were tested, each with different features and scenery. The original, encrypted and decrypted images are shown in Figures 10-14. In addition, the original, encrypted and decrypted images with the key values that were used in the present program can be downloaded from: [[https://figshare.com/articles/software/SecureVision_A_versatile_open-source_image_encryption_program_for_students/14946054](https://figshare.com/articles/software/SecureVision_A_versatile_open-source_image_encryption_program_for_students/14946054)]([https://figshare.com/articles/software/SecureVision_A_versatile_open-source_image_encryption_program_for_students/14946054](https://figshare.com/articles/software/SecureVision_A_versatile_open-source_image_encryption_program_for_students/14946054)) (accessed on 21 August 2021). Figures 10-14 show that the present program can satisfactorily encrypt and decrypt images. There were no significant losses of pixels or resolution in the decrypted images. The QR code example shown in Figure 14 demonstrates that the present program can fulfill stringent decryption requirements, since the restored QR code would not have worked in case of incorrect pixel positions or significant pixel losses. A comparative analysis between image encryption and decryption using our model and those using previously developed methods has been performed. The results from the previous works of [PERSON] [19] and [PERSON] et al. [1] were used in this comparison. The method proposed by [PERSON] [19] was based on pixel scrambling based on the chaotic map, while [PERSON] et al. [1] employed high-speed scrambling and pixel adaptive diffusion to encrypt images. Comparisons between their results and the results from our model are shown in Figures 15 and 16. The encryption and decryption times for a number of images with different resolutions are shown in Table 2. It is remarked that the reported duration is the overall time for 10 image layers (i.e., the program produces 10 encrypted images and merges these 10 image layers during decryption). Figure 14: A 714 \(\times\) 715 QR code image example used for testing the present program. Original, encrypted and decrypted images are shown (The QR code was generated on 3 July 2021 that directed to the main website of the City University of Hong Kong). Figure 15: Comparison between the encrypted images from previous work of [PERSON] [19] and our method. The decrypted image using our method is also shown. Figure 13: A 1280 \(\times\) 960 photograph example used for testing the present program. Original, encrypted and decrypted images are shown. Comparisons of some features (key space, GUI, speed and programming language) of techniques used in selected previous investigations and in the present work are shown in Table 3. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Image Size** & **Encryption Time (min:sms)** & **Decryption Time (min:sms)** \\ \hline
768 \(\times\) 1024 & 00:05:53 & 00:07:39 \\ \hline
1200 \(\times\) 1600 & 00:13:42 & 00:17:95 \\ \hline
2367 \(\times\) 1957 & 00:32:56 & 00:43:06 \\ \hline
2760 \(\times\) 2184 & 00:42:67 & 00:56:92 \\ \hline
3024 \(\times\) 4032 & 01:29:20 & 02:00:32 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Encryption and decryption times for different image resolutions (time shown is the total time taken for 10 image layers). Figure 16: Comparison between the encrypted images from previous work of [PERSON] et al. [1] and our method. The histogram for every image is shown below each figure.