Object detection and parameter estimation in point cloud is a lasting and current subject in CAD/CAM, reverse engineerind, computer vision, and digital factory. In this paper we present a software for fully automatic object detection and parameter estimation in unordered, incomplete and error-contamonated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting (ODF) play a fundamental role in each of the three modules, The ODF algorithms estimate the model parameters by minimizing the square sum of the shortesr distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.