A Survey on Feature Extraction Techniques for Shape based Object Recognition

@article{Patel2016ASO,
  title={A Survey on Feature Extraction Techniques for Shape based Object Recognition},
  author={Mitisha Narottambhai Patel and Purvi Tandel},
  journal={International Journal of Computer Applications},
  year={2016},
  volume={137},
  pages={16-20}
}
  • M. Patel, Purvi Tandel
  • Published 17 March 2016
  • Computer Science
  • International Journal of Computer Applications
Robotics is one of the research area in computer age. So, to make the robots as capable as humans, to allow them to interact with real environment so many algorithms are developed and will be developed. Some of those algorithms are developed in the area of computer vision to allow the robots for accurate recognition. In all those algorithms feature extraction technique is most important part of the algorithm. As the features are robust to different affine transformations like translation, scale… 
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References

SHOWING 1-10 OF 12 REFERENCES
Distinctive Image Features from Scale-Invariant Keypoints
  • D. Lowe
  • Computer Science
    International Journal of Computer Vision
  • 2004
TLDR
This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Color indexing
TLDR
It is demonstrated that color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models and that they can differentiate among a large number of objects.
Learning the shape manifold to improve object recognition
TLDR
This paper presents an approach for object recognition and shape retrieval in binary images by learning how to map the samples in high-dimensional observation space into the new manifold space so that the geometrically closer vectors belong to near semantics.
Edge image description using angular radial partitioning
The authors present a novel approach for image representation based on geometric distribution of edge pixels. Object segmentation is not needed, therefore the input image may consist of several
Review of shape representation and description techniques
TLDR
This paper identifies some promising techniques for image retrieval according to standard principles and examines implementation procedures for each technique and discusses its advantages and disadvantages.
Video surveillance object recognition based on shape and color features
  • Jun Wu, Zhitao Xiao
  • Computer Science
    2010 3rd International Congress on Image and Signal Processing
  • 2010
A new video surveillance object recognition algorithm is presented, in which improved invariant moments and length-width ratio of object are extracted as shape feature, while color histograms of
Fuzzy component based object detection
TLDR
A fuzzy approach to object detection that treats an object as a set of constituent components rather than a single entity is proposed and it is shown that the technique results in detection of most faces in a scale-invariant manner.
Recognition without Correspondence using Multidimensional Receptive Field Histograms
TLDR
This article presents a technique where appearances of objects are represented by the joint statistics of such local neighborhood operators, which represents a new class of appearance based techniques for computer vision.
Composed complex-cue histograms: An investigation of the information content in receptive field based image descriptors for object recognition
TLDR
An overall conclusion from this study is that compared to previously used lower-dimensional histograms, the use of composed complex-cue histograms of higher dimensionality reveals the co-variation of multiple cues and enables much better recognition performance, both with regard to the problems of recognizing previously seen objects from novel views and for classifying previously unseen objects into visual categories.
Distinctive Image Features from Scale-Invariant Keypoints
This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are ...
...
1
2
...