Laser scanner systems are widely used nowadays for objects and surface detection in several applications with different goals; some of them are fault detection, pattern recognition, object detection, and photogrammetry, among others. Cameras are commonly selected as collaborative elements for such systems; they are used to enhance the information quality acquired by the laser scanner. Details such as color, texture, temperature, and spatial data adjustment are some of the advantages of their application. Nevertheless, the data (commonly 3D point clouds) acquired by these systems still have to be post-processed to fit the requirements of specific applications. The proposed chapter will present a quick overview of similar scanning systems and their methodologies as the introductory section. Furthermore, it presents a laser scanner’s design, features, and mathematical formalism. The following section is divided into subchapters. The optical aspects of the scanner functioning are brought into the discussion. After, electromechanical analysis of the laser manipulator where friction compensation is done to achieve rotational stability and precision improvement. Then, the collaborative functioning and mathematical relationship between the laser scanner and stereo vision system is presented; this provides the scanning system with a so-called “multi-view.” Further data processing of the resulting measurements to increase the systems’ capability of surface characterization by texture and color identification is shown. The final section of the chapter lists possible applications for the proposed scanning system and provides advantages of the implementation. Proper conclusions to the chapter are presented in the final section.