aspg-3-3806-1791417842 20261008000402 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2025 20 1 Abdulaziz Saleh Alraddadi Department of Computer Science, Faculty of Science and Computer Engineering, Yanbu Branch, Taibah University, Yanbu, Saudi Arabia Essam O. Abdel-Rahman Department of Computer Science, Faculty of Science and Computer Engineering, Yanbu Branch, Taibah University, Yanbu, Saudi Arabia Department of Computer Science, Faculty of Computers and Information, Minia University, Minia, Egypt The current study introduces a trainable object detection model that can be taught to detect an object of a given class within an unconstrained scene. The researchers of the current study use this advanced system in the detection of Relics images, which involves a calculation of Local 3bit Binary Patterns (3bit-LBP). The key highlights of the current work include the integration and analyses of the utilization of the Multi-Support Vector Machine Classification (MSVMC) and Integral image computation analysis. The experimental outcomes of the current study indicate that the method of 3bit-LBP is superior to other methods in accuracy and stability, especially when images of different illumination and object rotation were tested. The researchers further conducted a comparative performance evaluation showing that the presented system gives better detection rates as compared to the conventional strategies, revealing the efficiency in real-world applications. Finally, it is important to note that the implications of the results can be applied to uses beyond just relic detection. To conclude, the current work advances the knowledge of how to improve the functionality of object recognition algorithms further in the context of image recognition systems. 2025 68 76 3806 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.200106 https://www.americaspg.com/journal/3/article/3806 https://www.americaspg.com/storage/articles/manuscripts/01M26EW5S5TGST4NA054HAGK8B.pdf