Face Image Retrieval System using Discrete Orthogonal Moments
John Patrick Ananth, V. Subbiah Bharathi · 2012
Abstract. Image Retrieval from large databases is an embryonic application predominantly in medical and forensic departments. Face image retrieval is quiet a thought-provoking task since face images can vary noticeably in terms of facial expressions, lighting conditions etc. In feature based image retrieval methods, the accuracy depends on the discrimination power of the features. In this work, orthogonal moments were employed as features for the retrieval task. Due to the orthogonal property, these moments are inherently non-redundant revealing good image representation capability. Racah moments defined in a non-uniform lattice are evidenced to be better than other orthogonal moments in terms of reconstruction error. Face image retrieval using Dual Hahn moment, Racah moment and Tchebicef moment features has been extensively experimented with YALE face database and FERET Database. The results divulge the effectiveness of orthogonal moment descriptors.