• Title/Summary/Keyword: Graph-cut

Search Result 101, Processing Time 0.023 seconds

A Study of the Use of step by preprocessing and Graph Cut for the exact depth map (깊이맵 향상을 위한 전처리 과정과 그래프 컷에 관한 연구)

  • Kim, Young-Seop;Song, Eung-Yeol
    • Journal of the Semiconductor & Display Technology
    • /
    • v.10 no.3
    • /
    • pp.99-103
    • /
    • 2011
  • The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using blue edge filter and graph cut algorithm. We do recommend the use of the simple sobel edge operator. The application of B band sobel edge operator over image demonstrates result with somewhat noisy (distinct border). The basic technique is to construct a specialized graph for the energy function to be minimized such that the minimum cut on the graph also minimizes the energy (either globally or locally). This method has the advantage of saving a lot of data. We propose a preprocessing effective stereo matching method based on sobel algorithm which uses blue edge information and the graph cut, we could obtain effective depth map.

DEM generation from an IKONOS stereo pair using EpiMatch and Graph-Cut algorithms

  • Kim, Tae-Jung;Im, Yong-Jo;Kim, Ho-Won;Kweon, In-So
    • Proceedings of the KSRS Conference
    • /
    • 2002.10a
    • /
    • pp.524-529
    • /
    • 2002
  • In this paper, we report the development of two DEM (digital elevation model) generation algorithms over urban areas from an IKONOS stereo pair. One ("EpiMatch") is originally developed for SPOT images and modified for IKONOS images. It uses epipolar geometry for accurate DEM generation. The other is based on graph-cut algorithm in 3D voxel space. This algorithm is believed to work better on height discontinuities than EpiMatch. An IKONOS image pair over Taejon city area was used for tests. Using ground control points obtained from differential GPS, camera model was set up and stereo matching applied. As a result, two DEMs over urban areas were produced. Within a DEM from EpiMatch small houses appear as small "cloudy" patches and large apartment and industrial buildings are visually identifiable. Within the DEM from graph-cut we could achieve better height information on building boundaries. The results show that both algorithms can generate DEMs from IKONOS images although more research is required on handling height discontinuities (for "EpiMatch") and on faster computation (for "Graph-cut").

  • PDF

Enhanced Graph-Based Method in Spectral Partitioning Segmentation using Homogenous Optimum Cut Algorithm with Boundary Segmentation

  • S. Syed Ibrahim;G. Ravi
    • International Journal of Computer Science & Network Security
    • /
    • v.23 no.7
    • /
    • pp.61-70
    • /
    • 2023
  • Image segmentation is a very crucial step in effective digital image processing. In the past decade, several research contributions were given related to this field. However, a general segmentation algorithm suitable for various applications is still challenging. Among several image segmentation approaches, graph-based approach has gained popularity due to its basic ability which reflects global image properties. This paper proposes a methodology to partition the image with its pixel, region and texture along with its intensity. To make segmentation faster in large images, it is processed in parallel among several CPUs. A way to achieve this is to split images into tiles that are independently processed. However, regions overlapping the tile border are split or lost when the minimum size requirements of the segmentation algorithm are not met. Here the contributions are made to segment the image on the basis of its pixel using min-cut/max-flow algorithm along with edge-based segmentation of the image. To segment on the basis of the region using a homogenous optimum cut algorithm with boundary segmentation. On the basis of texture, the object type using spectral partitioning technique is identified which also minimizes the graph cut value.

The Graph Partition Problem (그래프분할문제)

  • 명영수
    • Journal of the Korean Operations Research and Management Science Society
    • /
    • v.28 no.4
    • /
    • pp.131-143
    • /
    • 2003
  • In this paper, we present a survey about the various graph partition problems including the clustering problem, the k-cut problem, the multiterminal cut problem, the multicut problem, the sparsest cut problem, the network attack problem, the network disconnection problem. We compare those problems focusing on the problem characteristics such as the objective function and the conditions that the partitioned clusters should satisfy. We also introduce the mathematical programming formulations, and the solution approaches developed for the problems.

A study of a image segmentation by the normalized cut (Normalized cut을 이용한 Image segmentation에 대한 연구)

  • Lee, Kyu-Han;Chung, Chin-Hyun
    • Proceedings of the KIEE Conference
    • /
    • 1998.07g
    • /
    • pp.2243-2245
    • /
    • 1998
  • In this paper, we treat image segmentation as a graph partitioning problem. and use the normalized cut for segmenting the graph. The normalized cut criterion measures both the total dissimilarity between the different graphs as well as the total similarity within the groups. The minimization of this criterion can formulated as a generalized eigenvalues problem. We have applied this approach to segment static image. This criterion can be shown to be computed efficiently by a generalized eigenvalues problem

  • PDF

A Spanning Tree-based Representation and Its Application to the MAX CUT Problem (신장 트리 기반 표현과 MAX CUT 문제로의 응용)

  • Hyun, Soohwan;Kim, Yong-Hyuk;Seo, Kisung
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.18 no.12
    • /
    • pp.1096-1100
    • /
    • 2012
  • Most of previous genetic algorithms for solving graph problems have used a vertex-based encoding. We proposed an edge encoding based new genetic algorithm using a spanning tree. Contrary to general edge-based encoding, a spanning tree-based encoding represents only feasible partitions. As a target problem, we adopted the MAX CUT problem, which is well known as a representative NP-hard problem, and examined the performance of the proposed genetic algorithm. The experiments on benchmark graphs are executed and compared with vertex-based encoding. Performance improvements of the spanning tree-based encoding on sparse graphs was observed.

A Minimum Cut Algorithm Using Maximum Adjacency Merging Method of Undirected Graph (무방향 그래프의 최대인접병합 방법을 적용한 최소절단 알고리즘)

  • Choi, Myeong-Bok;Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.13 no.1
    • /
    • pp.143-152
    • /
    • 2013
  • Given weighted graph G=(V,E), n=|V|, m=|E|, the minimum cut problem is classified with source s and sink t or without s and t. Given undirected weighted graph without s and t, Stoer-Wagner algorithm is most popular. This algorithm fixes arbitrary vertex, and arranges maximum adjacency (MA)-ordering. In the last, the sum of weights of the incident edges for last ordered vertex is computed by cut value, and the last 2 vertices are merged. Therefore, this algorithm runs $\frac{n(n-1)}{2}$ times. Given graph with s and t, Ford-Fulkerson algorithm determines the bottleneck edges in the arbitrary augmenting path from s to t. If the augmenting path is no more exist, we determine the minimum cut value by combine the all of the bottleneck edges. This paper suggests minimum cut algorithm for undirected weighted graph with s and t. This algorithm suggests MA-merging and computes cut value simultaneously. This algorithm runs n-1 times and successfully divides V into disjoint S and V sets on the basis of minimum cut, but the Stoer-Wagner is fails sometimes. The proposed algorithm runs more than Ford-Fulkerson algorithm, but finds the minimum cut value within n-1 processing times.

Edge Extraction Algorithm for Mesh Data Based on Graph-cut Method and Principal Component Analysis (Graph-cut 과 주성분 분석을 이용한 Mesh 의 Edge 추출 알고리즘)

  • Han, HyeonDeok;Kim, HaeKwang;Han, Jong-Ki
    • Proceedings of the Korean Society of Broadcast Engineers Conference
    • /
    • 2021.06a
    • /
    • pp.204-207
    • /
    • 2021
  • LiDAR 장비 및 SfM 과 MVS 방법을 이용하여 생성된 point cloud 와 mesh 에는 항상 노이즈가 포함되어 있다. 이러한 노이즈를 제거하기 위해선 노이즈와 edge 를 효과적으로 구분해낼 수 있어야 한다. 노이즈를 제거하기 위해 mesh 로부터 edge 를 먼저 구분해낸 후 edge 에 해당하는 영역과 평면에 해당하는 영역에 서로 다른 필터를 사용하는 많은 연구들이 있지만 강한 노이즈가 포함된 mesh 에서는 edge를 잘 구분해내지 못하는 문제가 존재한다. 이러한 방법들은 mesh 로부터 edge 를 구분해내는 알고리즘의 성능이 노이즈를 제거하는 전체 알고리즘의 성능에 큰 영향을 주기 때문에 강한 노이즈에서도 edge 를 잘 구분해낼 수 있는 알고리즘이 필요하다. 본 논문에서는 PCA 와 graph-cut 을 이용하여 강한 노이즈가 포함된 mesh 에서 edge 영역을 추출하는 알고리즘을 제안한다.

  • PDF

ON PATHOS BLOCK LINE CUT-VERTEX GRAPH OF A TREE

  • Nagesh, Hadonahalli Mudalagiraiah
    • Communications of the Korean Mathematical Society
    • /
    • v.35 no.1
    • /
    • pp.1-12
    • /
    • 2020
  • A pathos block line cut-vertex graph of a tree T, written P BLc(T), is a graph whose vertices are the blocks, cut-vertices, and paths of a pathos of T, with two vertices of P BLc(T) adjacent whenever the corresponding blocks of T have a vertex in common or the edge lies on the corresponding path of the pathos or one corresponds to a block Bi of T and the other corresponds to a cut-vertex cj of T such that cj is in Bi; two distinct pathos vertices Pm and Pn of P BLc(T) are adjacent whenever the corresponding paths of the pathos Pm(vi, vj) and Pn(vk, vl) have a common vertex. We study the properties of P BLc(T) and present the characterization of graphs whose P BLc(T) are planar; outerplanar; maximal outerplanar; minimally nonouterplanar; eulerian; and hamiltonian. We further show that for any tree T, the crossing number of P BLc(T) can never be one.

Image Segmentation using Multi-scale Normalized Cut (다중스케일 노멀라이즈 컷을 이용한 영상분할)

  • Lee, Jae-Hyun;Lee, Ji Eun;Park, Rae-Hong
    • Journal of Broadcast Engineering
    • /
    • v.18 no.4
    • /
    • pp.609-618
    • /
    • 2013
  • This paper proposes a fast image segmentation method that gives high segmentation performance as graph-cut based methods. Graph-cut based image segmentation methods show high segmentation performance, however, the computational complexity is high to solve a computationally-intensive eigen-system. This is because solving eigen-system depends on the size of square matrix obtained from similarities between all pairs of pixels in the input image. Therefore, the proposed method uses the small-size square matrix, which is obtained from all the similarities among regions obtained by segmenting locally an image into several regions by graph-based method. Experimental results show that the proposed multi-scale image segmentation method using the algebraic multi-grid shows higher performance than existing methods.