• Corpus ID: 56348388

New techniques improving accuracy of computer vision technologies

@article{Dayalan2017NewTI,
  title={New techniques improving accuracy of computer vision technologies},
  author={Muthu Dayalan},
  journal={Journal of emerging technologies and innovative research},
  year={2017}
}
  • Muthu Dayalan
  • Published 1 September 2017
  • Computer Science
  • Journal of emerging technologies and innovative research
The computer vision technology has continued to evolve through advancement in researches. This has continually widened the computer vision and imaging processing to extended applications. This paper analyzes the technological advancement in these aspects. Machine vision system is among the emergent technologies, which digitizes the video images or information from a camera, processes the information to inspect the concerned object, and communicates with the system or the motion control [1] . 3D… 
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References

SHOWING 1-10 OF 43 REFERENCES
Recognition improvement through optimized spatial support methodology
TLDR
Experiments using a large database have demonstrated that the superiority of this methodology compared to that of previous methods has been demonstrated, and this methodology is capable of improving image recognition through optimizing segmentation results.
Empowering Simple Binary Classifiers for Image Set Based Face Recognition
TLDR
This paper suggests a different approach which does not resort to a single representation of an image set and an efficient classification strategy is developed which extends well-known simple binary classifiers for the task of multi-class image set classification.
VFM: Visual Feedback Model for Robust Object Recognition
TLDR
Inspired by the visual feedback, this work proposes a robust object recognition framework by designing a computational visual feedback model (VFM) between classification and detection that uses the “what” and “where” feedback to improve closeness and adaptiveness.
Context modeling in computer vision: techniques, implications, and applications
TLDR
This review is intended to introduce researchers in computer vision and image analysis to this increasingly important field as well as provide a reference for those who may wish to incorporate context modeling in their own work.
Threshold logic based low-level vision sparse object features
TLDR
A hardware friendly low-level sparse edge feature processing system is proposed for recognizing objects based on threshold logic of neurons, and the sparse selection of the features applies a modular and hierarchical processing inspired from the human neural system.
Visual descriptors for scene categorization: experimental evaluation
TLDR
This paper provides a critical review of visual descriptors used for scene categorization, from both methodological and experimental perspectives, and presents an empirical study conducted on four benchmark data sets assessing the classification accuracy and class separability of state-of-the-art visual descriptor.
Integrated vision-based system for efficient, semi-automated control of a robotic manipulator
TLDR
An integrated, computer vision-based system to operate a commercial wheelchair-mounted robotic manipulator (WMRM) and a gesture recognition interface system was developed specially for individuals with upper-level spinal cord injuries including object tracking and face recognition to function as an efficient, hands-free WMRM controller.
An Analysis of Linear Subspace Approaches for Computer Vision and Pattern Recognition
TLDR
An analysis of the “denoising capacity” of the singular value decomposition (SVD) of the LSA-based recognition system in a noise-corrupted environment and results should help one to predict aspects of performance and to design more optimal systems in computer vision.
Multiple thresholding and subspace based approach for detection and recognition of traffic sign
TLDR
This paper presents an Automatic Traffic Sign Detection and Recognition (ATSDR) system, involving three modules: segmentation, detection, and recognition, and demonstrates the robustness of traffic sign detection and recognition in real-world scenario.
3-D face recognition: features, databases, algorithms and challenges
TLDR
An extensive survey of recent 3-D face recognition techniques in terms of feature detection, classifiers as well as published algorithms that address expression and occlusion variation challenges is presented followed by critical comments on the published work.
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