Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a new method for removing specularity from face images so that albedo (diffuse reflectivity) can be accurately estimated. Our method utilizes common structural properties of face images to estimate the Lambertian component (including shadows) without using albedo, then specularity is separated as the positive component of the difference beten the estimated Lambertian component and the source image. Experimental results show that face-recognition performance is significantly improved by applying our new algorithm. Numerous previous face-recognition methods use 3D shape and albedo of an enrolled image for face recognition under variable pose and illumination conditions. Hover albedo used by the previous methods contained a residual of specularity from the enrolled image, which produced matching errors. Our algorithm is effective for solving this problem.
['Rui Ishiyama', 'Masato Tsukada']
I am writing a research paper on a idea Specularity removal for enhancing face recognition
[{"from": "human", "value": "I am writing a research paper on a idea Specularity removal for enhancing face recognition"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a new method for removing specularity from face images so that albedo (diffuse reflectivity) can be accurately estimated. Our method utilizes common structural properties of face images to estimate the Lambertian component (including shadows) without using albedo, then specularity is separated as the positive component of the difference beten the estimated Lambertian component and the source image. Experimental results show that face-recognition performance is significantly improved by applying our new algorithm. Numerous previous face-recognition methods use 3D shape and albedo of an enrolled image for face recognition under variable pose and illumination conditions. Hover albedo used by the previous methods contained a residual of specularity from the enrolled image, which produced matching errors. Our algorithm is effective for solving this problem."}]