Automatic red-eye effect removal using combined intensity and colour information

In this paper, we describe a robust and adaptive method to automatically detect and correct red‐eye effect in digital photographs. It improves the existing iris pair detection approaches by introducing a novel process of tuning eye candidate points which is followed by robust iris pair selection among the tuned candidates. Finally, a novel and highly effective red‐eye correction process is applied to the detected iris regions. The red‐eye correction scheme is adaptive to the severity of redness and results in high correction rate and improved visual appearance. The performance of the proposed method is compared with two existing automatic red‐eye correction methods and exhibits considerable performance gains. Additionally, the performance of eye detection part of the algorithm is separately evaluated on three well‐known images databases. The results have shown that the method is extremely robust in detection and correction of red‐eye artefact. The proposed method is designed to correct images without human intervention as the entire process from face detection to red‐eye correction is fully automated.