Medical Magnetic Resonance Images (MRI) is characterized by a composition of small differences in signal intensities between different tissues types. Thus ambiguities and uncertainties are introduced in image formation. In this paper, review of the current approaches in the tissue segmentation of MR Brain Images has been presented. The segmentation algorithms has been divided into four categories which is able to deal with different intensity non-uniformity as adaptive spatial Fuzzy C - means, Markov Random Field, Fuzzy connectedness method and atlas based re-fuzzy connectedness. The performance of these segmentation methods have been compared in terms of validation metric as dice similarity coefficient, overlap ratio and Jaccard coefficient. The comparison of all validation metric at different levels of intensity non-uniformity shows that adaptive Fuzzy C - means clustering segmentation method give better result in segmentation of brain tissue.

Digital images are very easy to manipulate, store, publish and secondary creation this juggle will lead to serious consequence in some applications such as military image, medical image. So, integrity of digital image must be authenticated. Tools that help us establish the authenticity and integrity of digital media are thus essential and can prove vital whenever questions are raised about the origin of an image and its content. To project authenticity of images semi fragile watermarking is very concerned by researchers because of its important function in content authentication. Semifragile watermarking aim to monitor contents of images not its representations. In present paper various semi fragile water marking algorithm are studied using some image quality matrices, insertion methods used, verification method. Finally some observations are given based on literature survey of algorithms and techniques of semifragile watermarking techniques.