PROBLEM DEFINITION In the era of evolving visual media, maintaining a polished image is vital for businesses and individuals. A leading South Korean enterprise faced the unique challenge of enhancing the images of 5,000 individuals, each with two pictures—one with a face mask and another without. The goal was to copy the area of the mouth and nose from the image without a face mask to the images with a face mask using Photoshop or Lightroom. They needed image masking services without utilizing machine learning or artificial intelligence. The company required assistance from a multilingual company that offered Photoshop image masking services to seamlessly merge the two images while ensuring tone adjustment without relying on machine learning or artificial intelligence. This project aimed to achieve an accuracy rate of 90%–95%. The South Korean company possessed a collection of images, each representing an individual with and without a face mask. Ensuring a consistent look across all images was a primary challenge, as it required precise alignment and integration of facial features, particularly the nose and mouth. The client needed assistance to merge the area around the mouth and nose from the "without a face mask" picture onto the corresponding "with a face mask" picture. Achieving a natural and seamless transition between the original face and the masked area while maintaining the same skin tone and texture was crucial. They required adjustments to ensure a consistent tone across the composite image. Their goal was to achieve an accuracy level of 90%-95% through traditional image editing techniques without utilizing machine learning or artificial intelligence. The South Korean company collaborated with a multilingual company specializing in Photoshop image masking services. Our team proposed a manual image editing approach using industry-standard tools like Adobe Photoshop and Lightroom. This method involved meticulous manual editing to copy the specific facial features from the "without a face mask" image and merge them seamlessly onto the "with a face mask" image. We conducted a thorough evaluation of the dataset to determine the scope of work and establish a project timeline. Our skilled graphic designers used Adobe Photoshop and Lightroom to meticulously extract the mouth and nose areas from the image without a face mask. After extraction of the desired facial features, the experts adjusted the skin tones and colors to create a harmonious blend between the two images. We adjusted the opacity and blending modes to integrate the features and create a natural appearance. To achieve the desired accuracy level of 90%–95%, we implemented rigorous quality control processes involving multiple reviews and revisions by skilled image editors.