Cyclones, with their high-speed winds and enormous quantities of rainfall, represent severe threats to global coastal regions. The ability to quickly and accurately identify cyclonic cloud formations is critical for the effective deployment of disaster preparedness measures. Our study focuses on a unique technique for precise delineation of cyclonic cloud regions in satellite imagery, concentrating on images from the Indian weather satellite INSAT-3D. This novel approach manages to achieve considerable improvements in cyclone monitoring by leveraging the image capture capabilities of INSAT-3D. It introduces a refined image processing continuum that extracts cloud attributes from infrared imaging in a comprehensive manner. This includes transformations and normalization techniques, further augmenting the pursuit of accuracy. A key feature of the study's methodology is the use of an adaptive threshold to correct complications related to luminosity and contrast; this enhances the detection accuracy of the cyclonic cloud formations substantially. The study further improves the preciseness of cloud detection by employing a modified contour detection algorithm that operates based on predefined criteria. The methodology has been designed to be both flexible and adaptable, making it highly effective while dealing with a wide array of environmental conditions. The utilization of INSAT-3D satellite images maximizes the performing capability of the technique in various situational contexts.