Transmitting the secret information by Steganography plays a vital role in Human Visual System (HVS). The carrier media such as image or audio or video can be used to hide the information. Steganalysis is a technique used to get rid of cheating, by identifying the hidden information from the carrier media. The identification of embedded information or message from the carrier media produces higher success rate to steganography methods. Image Steganography is the art of hiding the message or a file or an image by taking the image as carrier media. Based on the adaptable regions, the content is hidden and this method is termed as Adaptive image steganography. Dealing with retrieval of embedded content from the adaptable region of cover image is known to be Adaptive Image Steganalysis. The Blind Steganalysis is the ability to attack the stego image without the knowledge about steganography. Its Counter method, attacks the stego image by significant method used for steganography. In existing method, Enhanced canny edge detector is used to extract the features of the image better than other edge detectors, but smoothens the boundaries including noise and fails to identify the false edges. In the proposed method, Watershed method is used to segment the Adaptive regions from the stego image. The Markov Random Fields (MRF) extracts the features from the segmented adaptive region. The precision and recall is calculated after identifying the adaptive region with its payload location and hidden content using SVM (Support Vector Machine) classifier. An SVM is a binary classifier, classifies data by finding the best hyperplane which separates all data points of one class from the other class. After the classification and identification of payload location, the message is extracted from the hidden region by reversible two LSB (Least Significant Bit) bits.