Object recognition is important in many practical applications of computer vision. Traditional 2D methods are negatively affected byillumination, shadowing and viewpoint. 3D methods have the potential to solve these problems, because 3D models includegeometric properties of the objects. In this paper, 3D local feature based algorithms were used for 3D object recognition. The localfeature was keypoint. This study aimed to research facilities of keypoints for 3D object recognition. Keypoint is feature of object thatis detected by detector algorithms according to certain mathematical base. A recognition system was designed. For this purpose, adatabase that includes 3D model of objects was created. The algorithms were improved in MATLAB. The keypoints on the 3Dmodels were detected using keypoint detectors. These keypoints were described by keypoints descriptors. The descriptor algorithmsdetect geometrical relation between each point of point cloud and create a histogram. In the third step, the keypoints in different pointclouds are matched using the feature histograms obtained. Statistical methods are used to compare generated histograms. Thus, thetwo closest similar points between the different point clouds are matched. It is expected that the models with the most correspondingpoints belong to the same object. Euclidean distance between corresponding keypoints in the two point cloud is calculated. It hasbeen accepted that the points are shorter than 10 mm. The positional accuracy of the matched points has been examined. IterativeClosest Point (ICP) was applied to the matching point clouds for this purpose. As a result, the graphics were generated that showedcorrect matching ratio and root mean square error. As a result, there are different approaches about 3D object recognition inliterature. This study aimed to compare different keypoint detector and descriptor algorithms. Intrinsic Shape Signature (ISS) iskeypoint detector algorithms. Point Feature Histograms (PFH) and Fast Point Feature Histograms (FPFH) are keypoint descriptoralgorithms. The results of this study will provide guidance for future studies.