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This document is a retraction note for an article titled "Lip segmentation using localized active contour model with automatic initial contour" published in the journal Neural Computing & Applications. The article has been retracted by the Editor-in-Chief and the publisher due to concerns regarding compromised editorial handling and peer review process, inappropriate or irrelevant references, and not being in scope of the journal or guest-edited issue. The authors have not responded to correspondence from the publisher regarding this retraction. Springer Nature, the publisher, remains neutral in regards to jurisdictional claims and institutional affiliations. [Extracted from the article]

Lip-reading is one of important approaches for human-computer interaction (HCI). Its development would have a large range of applications, especially in augmented reality. Lip segmentation is the first and foremost step in the lip-reading system. Conventional method of region-based active contour model adopts the global information of image and is unable to perform well. In this paper, from a localized perspective, we introduce the methodology of localized active contour model (LACM) and, meanwhile, propose the method that using LACM to perform the lip segmentation with the initial contour automatically generated. The scope for active contour model is reduced to the local region that reduces the disturbances of unrelated factors. The experimental results demonstrate the method adopts this model would dramatically improve the robustness for lip segmentation. On this basis, we analyze the influence of initial contours and local radiuses, study the efficiencies under different initial contours and compare it with the conventional active contour model which adopts the global information. [ABSTRACT FROM AUTHOR]