Developed and integrated an Intel IPP-backed image resizing feature for the opencv/opencv repository, focusing on performance and scalability in image processing workflows. The implementation leveraged C++ and parallel programming techniques to enable efficient resizing with support for multiple interpolation methods, reducing CPU load and improving throughput for resizing-heavy pipelines. This end-to-end solution was fully integrated into the core image resizing path, aligning with repository standards and laying the foundation for broader CPU-side optimizations. The work demonstrated a strong command of image processing and parallelization, delivering a flexible and efficient approach to image resizing within the OpenCV ecosystem.