A brain tumor is a lethal disease caused by the irregular growth of abnormal cells in the brain. Investigation of brain tumors with precise size, shape, and location is the most difficult task for medical experts, due to the noise inherited into the image during imaging. Also, investigating corrupted images due to instrumental errors is tedious and may lead to false detection of the tumor. To overcome the above-stated problems, an effective approach is made to detect the tumor by processing the MR images. The system initially pre-processes the acquired MR images and segments the regions using the manual threshold method, and the morphology of the tumor will be studied based on the shape, and texture-based parameters to identify the area, shape, and the region of tumor. This system efficiently detects the tumor on the brain tumor dataset and gives informative inputs about the tumor to the pathologist for diagnosis.