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With the rise in construction activities, there arises a necessity to devise a dependable and streamlined method for assessing objects and estimating their materials without requiring the presence of a surveyor. Historically, this task has fallen to surveyors utilizing measuring tapes and similar tools to ascertain the dimensions of doors and windows. Nevertheless, this conventional approach can prove time-intensive and susceptible to errors, resulting in inaccuracies in material estimations and potential budget overruns. This research endeavors to formulate a precise and efficient methodology for object measurement employing image processing and computer vision techniques. Various methodologies, including image capture, edge detection, and segmentation, are explored for detecting and quantifying object parameters within images. Crucially, validating the proposed methodology through comparison with measurements conducted by a surveyor is imperative to ensure its accuracy and reliability. The study's potential for cost-effectiveness and efficiency in industrial and commercial settings is also underscored. The project comprises of four stages:
 The object will be identified and classified from images.
 The size and dimensions of region of interest will be computed.
 The required material and resources will be estimated in terms of hardware and cost.
 Draft invoice will be generated.