Contour Generation Algorithm Research Articles

Contour generation algorithm for projection mask stereolithography 3D printing process

Projection mask stereolithography is a latest technology in 3D printing industry. It relies on UV projection to cure the photocurable resin layer-by-layer to build the solid 3D object. The projections are generated from tessellated STL CAD model using contour generation algorithm that generates 2D contours as the projection mask. The computational of the algorithm consumes a lot of memory for high-resolution printing. Low-resolution causes the stair-case effect to visibly appear on the printed model. Using real-time contour generation algorithm reduces the memory consumption and retains the high-resolution printing quality and accuracy. Pixel line mapping algorithm is implemented on the generated line segments to scale the line segments with respect to the display resolution of the projection device. Contour loop algorithm connects each of these pixel line segments into multiple closed-loop contours. The algorithms are implemented on an Alien STL model having 150350 facets. It is found that the pixel mapping algorithm correctly scales the model while retaining the aspect ratio of the model. The result of contour loop algorithm shows that the mean contour loop execution time is 0.87 milliseconds which is relevant for real-time application.

A Layered Section Contour Generation Algorithm for Additive Manufacturing Parts with Complex Surfaces

A Layered Section Contour Generation Algorithm for Additive Manufacturing Parts with Complex Surfaces

SU‐E‐T‐488: Incorporating In‐House Treatment Planning Software Into Clinical Auto‐Planning Workflow

Purpose:To report the process of incorporating in‐house software tools into clinical workflow of auto‐planning with the objectives of achieving efficiency and quality plans.With multi‐year research and development, we built in‐house software suites of various GPU‐based components of a treatment planning system (TPS), which includes DICOM import/export, various deformable image registration (DIR) and contour generation algorithms, multiple dose calculators and optimizers, and plan generation with or without reference guidance. However, to meet clinical quality, we need to further test the robustness of the tools, streamline the processes, including the front and back end processes.Methods:We build an in‐house patient database management system and collect patient data of various delivery modalities, such as IMRT, VMAT, etc., and of various disease sites, such as head and neck, breast, lung, prostate, etc., to be used as repository for part of simulating the clinical workflow and subsequent testing.A unit‐testing tool was developed that any input parameter can be loaded from a configuration file for batch processing. Modular inputs and outputs were part of the design, and button clicking and human interaction can be bypassed.Results:The database with various delivery modalities and various disease sites allows the auto‐planning tools to test on variety of cases. The unit‐testing tools allow mass data processing and analysis. As testing showed, the whole auto‐planning process can be done in a couple of minutes without any human interaction.Conclusion:A database and unit‐testing tools are essential in incorporating the in‐house software into the clinical auto‐planning workflow and greatly facilitate the implementation by allowing component testing and mass data processing and analysis. Thus, desired functional behavior may be ensured, the impact of any code modification can be more easily identified, and any unintended alteration can be avoided.

Implementation and performance optimization of a parallel contour line generation algorithm

This paper introduces a parallel contour line interpolation algorithm from Digital Elevation Model (DEM). Contour generation from DEM is the basic task of the computer-aided mapping and one of the most important applications of DEM. With the increasing of DEM resolution, the Digital Terrain Analysis (DTA) has become one of the computing-intensive tasks in GIS. Many studies have been done on the implementation of parallel DTA algorithms based on different parallel hardware and software. In this paper, we use the open source GIS toolkit to implement a parallel contour generation algorithm. The Message Passing Interface (MPI) standard is used for the parallel algorithm programming. A slackly LAN (Local Area Network)-connected windows cluster is setup to implement and test the parallel contour line generation algorithm. The performance optimization method for the parallel algorithm is specifically discussed, including data redundancy method, group communication, packaging collection of results, and memory optimization method for results merging. The experimental results show the capacity and potential to implement the parallel GIS algorithms based on open source GIS toolkit in the LAN-connected PC environment.

GPU-based leaves contour generation algorithm

The implementation and optimization of the traditional contour generation algorithms are always proposed for the common processor. When processing high resolution images, the performance often exists low efficiency. A new graphics processing unit (GPU)-based algorithm is proposed to get the clear and integrated contour of leaves. Firstly we implement the classic Sobel operator of edge detection in GPU. Then a simple and effective method is designed to remove the fake edge and a heuristic algorithm is used to repair the broken edge. It is proved by the experiments that the results of our algorithm are natural and realistic in terms of morphology and can be good materials for the virtual plant.

A Novel Contour Generation Algorithm for Surface Reconstruction From Dexel Data

This paper presents a method of reconstructing a triangular surface patch from dexel data generated by ray casting to represent solid models for applications, such as virtual sculpting and numerically controlled (NC) machining simulation. A novel contour generation algorithm is developed to convert dexel data into a series of planar contours on parallel slices. The algorithm categorizes the dexels on two adjacent rays into different groups by using a “grouping” criterion. The dexel points in the same group are connected using a set of rules to form subboundaries. After checking the connections among all the dexel points on one slice, a connection table is created and used to obtain the points of connection in a counterclockwise sequence for every contour. Finally, the contours on all the parallel slices are tiled to obtain triangular facets of the boundary surface of the 3D object. Computational costs and memory requirements are analyzed, and the computational complexity analysis is verified by numerical experiments. Example applications are given to demonstrate the described method.

Hybrid image processing for robust extraction of lean tissue on beef cut surfaces

Abstract A hybrid image processing system which automatically distinguishes lean tissues in the image of a complex beef cut surface and generates the lean tissue contour has been developed. Because of the inhomogeneous distribution and fuzzy pattern of fat and lean tissues on the beef cut, conventional image segmentation and contour generation algorithms suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network to enhance the robustness of processing. The system is composed of pre-network, network, and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted to a grid pattern image, whose grid was formed as 4 × 4 pixel size. At the network stage, the normalized gray value of each grid image was taken as the network input. The pre-trained network generated the grid image output of the isolated lean tissue. A sequence of post-network processing was conducted to obtain the detailed contour of the lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human-like robust object segmentation and contour generation for the complex, fuzzy and irregular image.