scholarly journals Speed-up Line Detection Approach for Large-size Document Images by Parallel Pixel Scanning and Hough Space Minimization

2016 ◽  
Author(s):  
H. Waruna H. Premachandra ◽  
Chinthaka Premachandra ◽  
Chandana Dinesh Parape ◽  
Hiroharu Kawanaka
Keyword(s):  
Line Detection ◽  
Document Images ◽  
Large Size ◽  
Hough Space ◽  
Detection Approach ◽  
Speed Up

Speed-up ellipse enclosing character detection approach for large-size document images by parallel scanning and Hough transform

2015 ◽  
Vol 8 (1) ◽  
pp. 371-378 ◽  
Author(s):  
H. Waruna H. Premachandra ◽  
Chinthaka Premachandra ◽  
Chandana Dinesh Parape ◽  
Hiroharu Kawanaka
Keyword(s):  
Hough Transform ◽  
Document Images ◽  
Large Size ◽  
Detection Approach ◽  
Speed Up

scholarly journals Natural Feature Detection on Mobile Phones with 3D FAST

2010 ◽  
Vol 9 (4) ◽  
pp. 29-34 ◽  
Author(s):  
Achim Weimert ◽  
Xueting Tan ◽  
Xubo Yang
Keyword(s):  
Feature Detection ◽  
Feature Matching ◽  
Hessian Matrix ◽  
Detection Algorithm ◽  
Scale Invariant ◽  
Natural Feature ◽  
Detection Approach ◽  
Scale Levels ◽  
Speed Up ◽  
Low Performance

In this paper, we present a novel feature detection approach designed for mobile devices, showing optimized solutions for both detection and description. It is based on FAST (Features from Accelerated Segment Test) and named 3D FAST. Being robust, scale-invariant and easy to compute, it is a candidate for augmented reality (AR) applications running on low performance platforms. Using simple calculations and machine learning, FAST is a feature detection algorithm known to be efficient but not very robust in addition to its lack of scale information. Our approach relies on gradient images calculated for different scale levels on which a modified9 FAST algorithm operates to obtain the values of the corner response function. We combine the detection with an adapted version of SURF (Speed Up Robust Features) descriptors, providing a system with all means to implement feature matching and object detection. Experimental evaluation on a Symbian OS device using a standard image set and comparison with SURF using Hessian matrix-based detector is included in this paper, showing improvements in speed (compared to SURF) and robustness (compared to FAST)

scholarly journals Humanitarian Demining: Reality and the Challenge of Technology – The State of the Arts

10.5772/5699 ◽  
2007 ◽  
Vol 4 (2) ◽  
pp. 19 ◽  
Author(s):  
Maki K. Habib
Keyword(s):  
Cost Effective ◽  
Mine Detection ◽  
Local Conditions ◽  
Team Cooperation ◽  
Humanitarian Demining ◽  
The Arts ◽  
Detection Approach ◽  
Speed Up ◽  
Technical Features ◽  
Processing Techniques

In the context of humanitarian demining it is essential to have a reliable and accurate sensor or an integration of heterogeneous/homogeneous sensors with efficient and reliable data fusion and processing techniques. In addition, it is necessary to overcome the constrain on the resources to speed up the demining process in terms of time, cost, and safety enhancement of personnel and operation. A portable handheld mine detection approach to sensor movement is slow and hazardous for individual deminers. Armored vehicles may not thoroughly protect the occupants and may be of only limited usefulness in off-road operations. Robotized solutions with effective sensing capabilities properly sized with suitable modularized mechanized structure and well adapted to local conditions of minefields can greatly improve the safety of personnel as well as work efficiency and flexibility. Such intelligent and flexible machines can speed the clearance and perform verifying processes when used in combination with handheld mine detection tools. Furthermore, the use of many robots working and coordinating their movement will improve the productivity of the overall mine detection process through the use of team cooperation and coordination. This paper evaluates the available mine clearance technologies and disscusses their development efforts and limitations to automate tasks related to demining process. In addition, it introduces technical features and design capabilities of a mobile platform needed to accelerate the demining process and achieve safety with cost effective measures.

A New Multiscale Line Detection Approach for Aerial Image with Complex Scene

2006 ◽  
Author(s):  
Jing Wang ◽  
Takeshi Ikenaga ◽  
Satoshi Goto ◽  
Kazuo Kunieda ◽  
Makoto Iwata ◽  
...  
Keyword(s):  
Aerial Image ◽  
Line Detection ◽  
Complex Scene ◽  
Detection Approach

scholarly journals Two particle picking procedures for filamentous proteins: SPHIRE-crYOLO filament mode and SPHIRE-STRIPER

2020 ◽  
Author(s):  
Thorsten Wagner ◽  
Luca Lusnig ◽  
Sabrina Pospich ◽  
Markus Stabrin ◽  
Fabian Schönfeld ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Molecular Complexes ◽  
High Accuracy ◽  
The Other ◽  
Line Detection ◽  
Data Sets ◽  
Detection Approach ◽  
Selection Of

AbstractStructure determination of filamentous molecular complexes involves the selection of filaments from cryo-EM micrographs. The automatic selection of helical specimens is particularly difficult and thus many challenging samples with issues such as contamination or aggregation are still manually picked. Here we present two approaches for selecting filamentous complexes: one uses a trained deep neural network to identify the filaments and is integrated in SPHIRE-crYOLO, the other one, called SPHIRE-STRIPER, is based on a classical line detection approach. The advantage of the crYOLO based procedure is that it accurately performs on very challenging data sets and selects filaments with high accuracy. Although STRIPER is less precise, the user benefits from less intervention, since in contrast to crYOLO, STRIPER does not require training. We evaluate the performance of both procedures on tobacco mosaic virus and filamentous F-actin data sets to demonstrate the robustness of each method.

scholarly journals OPTIMIZE, UPGRADE OR INVEST IN A NOVEL DRYER? – A BRICK FACTORY CASE STUDY

2021 ◽  
Vol 1 (2) ◽  
pp. 62-70
Author(s):  
Miloš R. Vasić ◽  
◽  
Milica V. Vasić ◽  
Keyword(s):  
Raw Materials ◽  
Ambient Air ◽  
Raw Material ◽  
Drying Process ◽  
Tunnel Dryer ◽  
Large Size ◽  
Speed Up ◽  
The One ◽  
Industrial Level ◽  
Energy Balances

Drying has an enormous impact on the quality of final masonry clay elements. The accumulated knowledge about modeling the drying process, as well as the registered progress in computing the coupling between the heat and mass transfer during the last decade has reached the applicative industrial level. The available novel commercial drying solutions have dropped the drying cycle to 5 hours for hollow clay products and up to 9 hours for clay blocks of large size and weight. The ability to speed up the drying process also strongly depends on the properties of the raw materials. The decision on optimization of the existing dryer and its upgrade or investment in a novel drying facility must be experimentally validated. Results of the one-month monitoring and analysis of the production process in one Serbian brick factory including the material and energy balances are given in this paper. Based on the collected data, raw material limitations and costs of the novel dryer the existing tunnel dryer upgrade and the minimization of the "false" ambient air into the dryer are proposed.

scholarly journals A Continuous Terminal Sliding-Mode Observer-Based Anomaly Detection Approach for Industrial Communication Networks

Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 124
Author(s):  
Long Xu ◽  
Wei Xiong ◽  
Minghao Zhou ◽  
Lei Chen
Keyword(s):  
Anomaly Detection ◽  
Communication Networks ◽  
Sliding Mode ◽  
Traffic Monitoring ◽  
Sliding Mode Observer ◽  
Terminal Sliding Mode ◽  
Finite Time Stability ◽  
Industrial Networks ◽  
Detection Approach ◽  
Speed Up

Dynamic traffic monitoring is a critical part of industrial communication network cybersecurity, which can be used to analyze traffic behavior and identify anomalies. In this paper, industrial networks are modeled by a dynamic fluid-flow model of TCP behavior. The model can be described as a class of systems with unmeasurable states. In the system, anomalies and normal variants are represented by the queuing dynamics of additional traffic flow (ATF) and can be considered as a disturbance. The novel contributions are described as follows: (1) a novel continuous terminal sliding-mode observer (TSMO) is proposed for such systems to estimate the disturbance for traffic monitoring; (2) in TSMO, a novel output injection strategy is proposed using the finite-time stability theory to speed up convergence of the internal dynamics; and (3) a full-order sliding-mode-based mechanism is developed to generate a smooth output injection signal for real-time estimations, which is directly used for anomaly detection. To verify the effectiveness of the proposed approach, the real traffic profiles from the Center for Applied Internet Data Analysis (CAIDA) DDoS attack datasets are used.

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