The study about object recognition especially for three dimensional (3D) objects is still running and developed even until now. Therefore, the main purpose of this final thesis research is to make a 3D object contour reconstruction so may help to contribute in the development. The basic objectives are to analyze the data from the scanning process, to store coordinate points and its spline interpolation that represent the object’s contour, and to analyze the 3D grid image quality of the system. The system is only able to measure outer contour of the object and its dimension is also limited, so does its color and reflectivity is affecting the measured data, and the sensor is somewhat prone to noises. The scanner tool is mainly consists of infrared proximity sensor and rotatable disk for the object that actuated by stepper motors individually. For the scanning process, object is placed on the disk and it will rotate as the sensor measure the distance to the object’s surface each step. Every full rotation completed then the sensor will move upward to scan the next horizontal layer. Acquired data will be processed to Cartesian coordinate points that represents contour of the object and saved in two dimensional arrays for its each (x, y) components and horizontal layers. Then that data of points will be plotted to picture boxes to show the first six horizontal layers from the object’s contour. Afterward there would be cubic spline interpolation to calculate curve equations that connects each point for each layer. Finally, the data will be plotted in three dimensional grid pictures. As the result, the system is able to recognize most of the object contour. The shown 3D image is also indicated that the system is able to acquire data which resembles the objects. Subsequently, it can be concluded that the system is success to achieve the basic purpose of the research. For the next development, to get more accurate data a better proximity sensor is needed, also a more efficient program method to process and plot the data.