Bilgisayar ve Bilişim Fakültesi Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.13091/10834

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Now showing 1 - 4 of 4

Citation - WoS: 3
Citation - Scopus: 4
Approaches To Automated Land Subdivision Using Binary Search Algorithm in Zoning Applications
(Ice Publishing, 2022) Koç, İsmail; Çay, Tayfun; Babaoğlu, İsmail
The planned development of urban areas depends on zoning applications. Although zoning practices are performed using different techniques, the parcelling operations that shape the future view of the city are the same. Preparing the parcelling plans is an important step that has a direct impact on ownership structure and reallocation. Parcelling operations are traditionally handled manually by a technician. This is a serious problem in terms of time and cost. In this study, by taking the zoning legislation, the production of a pre-land subdivision plan has been automatically performed for a region of Konya, which is one of the major cities in Turkey. The parcelling processes have been performed in three different ways: the first parcelling technique is parcelling with edge values, the second is parcelling with area values and the third is parcelling using both edge and area values together. For the entire parcelling process, the area of the parcel has been calculated using the Gauss method. Moreover, to effectively determine the boundaries and to calculate the parcel area in the parcelling process, the binary search technique has been used in all the methods. The experimental results show that the parcelling operations were carried out very quickly and successfully.
Citation - WoS: 24
Citation - Scopus: 34
Boundary Constrained Voxel Segmentation for 3d Point Clouds Using Local Geometric Differences
(PERGAMON-ELSEVIER SCIENCE LTD, 2020) Sağlam, Ali; Makineci, Hasan Bilgehan; Baykan, Nurdan Akhan; Baykan, Ömer Kaan
In 3D point cloud processing, the spatial continuity of points is convenient for segmenting point clouds obtained by 3D laser scanners, RGB-D cameras and LiDAR (light detection and ranging) systems in general. In real life, the surface features of both objects and structures give meaningful information enabling them to be identified and distinguished. Segmenting the points by using their local plane directions (normals), which are estimated by point neighborhoods, is a method that has been widely used in the literature. The angle difference between two nearby local normals allows for measurement of the continuity between the two planes. In real life, the surfaces of objects and structures are not simply planes. Surfaces can also be found in other forms, such as cylinders, smooth transitions and spheres. The proposed voxel-based method developed in this paper solves this problem by inspecting only the local curvatures with a new merging criteria and using a non-sequential region growing approach. The general prominent feature of the proposed method is that it mutually one-to-one pairs all of the adjoining boundary voxels between two adjacent segments to examine the curvatures of all of the pairwise connections. The proposed method uses only one parameter, except for the parameter of unit point group (voxel size), and it does not use a mid-level over-segmentation process, such as supervoxelization. The method checks the local surface curvatures using unit normals, which are close to the boundary between two growing adjacent segments. Another contribution of this paper is that some effective solutions are introduced for the noise units that do not have surface features. The method has been applied to one indoor and four outdoor datasets, and the visual and quantitative segmentation results have been presented. As quantitative measurements, the accuracy (based on the number of true segmented points over all points) and F1 score (based on the means of precision and recall values of the reference segments) are used. The results from testing over five datasets show that, according to both measurement techniques, the proposed method is the fastest and achieves the best mean scores among the methods tested. (C) 2020 Elsevier Ltd. All rights reserved.
Citation - WoS: 9
Citation - Scopus: 15
Clustering-Based Plane Refitting of Non-Planar Patches for Voxel-Based 3d Point Cloud Segmentation Using K-Means Clustering
(INT INFORMATION & ENGINEERING TECHNOLOGY ASSOC, 2020) Sağlam, Ali; Makineci, Hasan Bilgehan; Baykan, Ömer Kaan; Baykan, Nurdan Akhan
Point cloud processing is a struggled field because the points in the clouds are three-dimensional and irregular distributed signals. For this reason, the points in the point clouds are mostly sampled into regularly distributed voxels in the literature. Voxelization as a pretreatment significantly accelerates the process of segmenting surfaces. The geometric cues such as plane directions (normals) in the voxels are mostly used to segment the local surfaces. However, the sampling process may include a non-planar point group (patch), which is mostly on the edges and corners, in a voxel. These voxels can cause misleading the segmentation process. In this paper, we separate the non-planar patches into planar sub-patches using k-means clustering. The largest one among the planar sub-patches replaces the normal and barycenter properties of the voxel with those of itself. We have tested this process in a successful point cloud segmentation method and measure the effects of the proposed method on two point cloud segmentation datasets (Mosque and Train Station). The method increases the accuracy success of the Mosque dataset from 83.84% to 87.86% and that of the Train Station dataset from 85.36% to 87.07%.
Citation - WoS: 6
Citation - Scopus: 7
A Novel Metaheuristic Algorithm by Efficient Crossover Operator for Land Readjustment
(PERGAMON-ELSEVIER SCIENCE LTD, 2022) Koç, İsmail; Çay, Tayfun; Babaoğlu, İsmail
Land readjustment and reallocation (LR) applications are complex and difficult real-world problems involving many different criteria. By considering these criteria, it is very difficult and takes a long time to be solved manually by an expert. Since the search space of these problems is very large, solution of these problems requires meta-heuristic optimization algorithms instead of classical methods in order to acquire more robust, acceptable and qualified solutions. Considering the meta-heuristic approaches, the algorithm needs an objective function that can make the right decision and evaluate the solutions most reasonably among the candidate solutions. Using the proposed objective function, the quality of the distribution and subdivision plans will be automatically evaluated and compared without the need for an expert. In this study, an objective function which considers all the criteria in the LR problems is proposed. In addition, unlike the available crossover operators used in metaheuristic algorithms in the literature, two different parcel-based crossover operators called Classical (CPC) and Intelligent (IPC) Parcel-Based Crossover Operators are proposed. While CPC performs the distribution of the owners to the predetermined parcel randomly, IPC makes this operation with a greedy approach rather than randomly. According to this approach, if the shareholder and distance values after the crossover operation would be better than the existing ones, the crossover operation is performed. Otherwise, this operation is cancelled. By using the proposed objective function and crossover operators, artificial bee colony (ABC), particle swarm optimization (PSO) and differential evolution (DE) algorithms are run under equal conditions on a real project site, and the obtained results are compared with the official results obtained by a technician in the study. In addition, since there will be so many zoning blocks of different sizes and shapes on a real project site, it is very possible to have gaps or overflows in the blocks of subdivision plans obtained from the algorithms. Therefore, the gaps and overflow areas in the blocks can be completely eliminated by utilizing an Expert System developed specifically for LR problems called LRES, and as a result, the solutions obtained from the algorithms can be directly applicable in real life by the LRES. It's clearly seen from the experimental studies that all of the results obtained by using the algorithms based on LRES are much more effective than the official results obtained by a technician in terms of both solution quality and speed. In addition, among the evaluated algorithms, it is observed that the PSO algorithm presents much more effective and robust results than results of the other algorithms. Moreover, as a consequence of the algorithms using the IPC presents much more successful results than the results of the algorithms using CPC, it can be used as a very effective alternative crossover operator for land use problems.

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Browsing Bilgisayar ve Bilişim Fakültesi Koleksiyonu by Department "Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Harita Mühendisliği Bölümü"