# An Efficient System for Automatic Blood Type Determination Based on Image Matching Techniques
## 6 Conclusions and Future Work  
In this paper, an automated system was created adopting the ORB algorithm in order to provide an accurate diagnostic support for blood type determination. The designed system proved that it is invariant to the variations of the brightness and can detect different agglutination patterns. Furthermore, it provides the results with short time and a high accuracy of 99.6%. The system was evaluated using a total of 500 different images that were partitioned into 1500 images of blood spots. It was compared with other systems based on the standard deviation, the SIFT algorithm, and the SURF algorithm. The evaluation showed that the approaches have an accuracy of 59%, 69%, 84.6%, and 94%, respectively, and an average processing time of 0.08, 7.77, 0.775, and 0.167 s, respectively. The ORB algorithm was further optimized in order to improve accuracy from 94% to 99.6% while sacrificing the addition of 83 ms.  
As for future work, a user-friendly mobile application will be developed based on the optimized ORB algorithm to completely dispense with the PC to analyze blood images. This application will help the laboratory technicians and civil defense paramedics to automatically determine blood type with high accuracy and short time avoiding human error. The application could be connected to a centralized database in order to collect medical information for people in Palestine. The database could be accessed by hospitals and medical centers to provide vital information in a short amount of time. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Actual Class/Predicted Class** & **A+** & **A\(-\)** & **B+** & **B\(-\)** & **AB+** & **AB\(-\)** & **O+** & **O\(-\)** & **Total** \\ \hline A+ & 171 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 171 \\ \hline A\(-\) & 1 & 28 & 0 & 0 & 0 & 0 & 0 & 0 & 29 \\ \hline B+ & 0 & 0 & 69 & 0 & 0 & 0 & 0 & 0 & 69 \\ \hline B\(-\) & 0 & 0 & 0 & 7 & 0 & 0 & 0 & 0 & 7 \\ \hline AB\(+\) & 0 & 0 & 0 & 0 & 37 & 0 & 0 & 0 & 37 \\ \hline AB\(-\) & 0 & 0 & 0 & 0 & 0 & 5 & 0 & 0 & 5 \\ \hline O\(+\) & 0 & 1 & 0 & 0 & 0 & 0 & 161 & 0 & 162 \\ \hline O\(-\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 20 & 20 \\ \hline Total & 172 & 29 & 69 & 7 & 37 & 5 & 161 & 20 & 500 \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Confusion matrix for the optimized ORB algorithm over the 500 blood samples. Figure 23: Results summary for the evaluated systems over the 500 samples. **Author Contributions:** Conceptualization, N.O. and F.M. ; methodology, N.O., F.O. and M.S. ; software, N.O., F.O. and M.S. ; validation, A.T. and N.O. ; formal analysis, N.O. ; investigation, F.O. and M.S. ; resources, N.O. ; data curation, N.O., F.O. and M.S. ; writing--original draft preparation, N.O., F.M. and Y.D. ; writing--review and editing, A.T., N.O., F.M. and Y.D. ; visualization, N.O. and A.T.; supervision, N.O. and F.M. ; project administration, N.O. ; funding acquisition, N.O., F.M. and Y.D. All authors have read and agreed to the published version of the manuscript. This research was funded by the Deanship of Scientific Research at An-Najah National University, grant number ANNU-1920-Sc001. Ethical review and approval were waived for this study, due to the fact that the blood samples were collected anonymously. No identification or personal information were recorded. Patient consent was waived due to the fact that the blood samples were collected anonymously. No identification or personal information were recorded. Data available in a publicly accessible repository that does not issue DOIs. This data can be found here: [[https://earchive.najah.edu/media-email-link/88533?expires=1630145030&signature=aa69219224041d314](https://earchive.najah.edu/media-email-link/88533?expires=1630145030&signature=aa69219224041d314) ab7289 de51f33d97462e2912a6 df1b31 de83858 bd9 cd4]([https://earchive.najah.edu/media-email-link/88533?expires=1630145030&signature=aa69219224041d314](https://earchive.najah.edu/media-email-link/88533?expires=1630145030&signature=aa69219224041d314) ab7289 de51f33d97462e2912a6 df1b31 de83858 bd9 cd4).