Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/3806 2018 2018 Department of Computer Science, Faculty of Science and Computer Engineering, Yanbu Branch, Taibah University, Yanbu, KSA Essam Essam Department of Computer Science, Faculty of Science and Computer Engineering, Yanbu Branch, Taibah University, Yanbu, KSA; Department of Computer Science, Faculty of Computers and Information, Minia University, Minia, Egypt Essam O. Abdel Abdel-Rahman 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 2025 68 76 10.54216/FPA.200106 https://www.americaspg.com/articleinfo/3/show/3806