scholarly journals Survey on Shape Description and Recognition Techniques

2020 ◽  
pp. 229-234
Author(s):  
Aswathi A S ◽  
Philumon Joseph
Keyword(s):  
Object Recognition ◽  
Image Retrieval ◽  
Shape Description ◽  
Visual Feature ◽  
Shape Features ◽  
Survey Paper ◽  
Advantages And Disadvantages

The images have to be described by certain features. The shape is an important visual feature in understanding an image, that remains stable in spite of changes in an object's illumination, color, and texture. So shape features have been applied in object recognition tasks. There are many shape description and recognition techniques in the literature. This survey paper provides an overview of description and recognition techniques and examines implementation procedures for each technique and its advantages and disadvantages. Finally, identify some techniques for image retrieval according to standard principles.

scholarly journals Volume Decomposition for Hierarchical Skeletonization

2009 ◽  
Vol 8 (1) ◽  
pp. 89-97 ◽  
Author(s):  
Xiaopeng Zhang ◽  
Jianfei Liu ◽  
Marc Jaeger ◽  
Zili Li
Keyword(s):  
Initial Data ◽  
Hierarchical Structure ◽  
Shape Description ◽  
Shape Features ◽  
Volume Data ◽  
Volume Decomposition ◽  
The Hierarchical Structure

Hierarchical skeletons and shape components are important shape features, and they are useful for shape description and shape understanding. Techniques to extract shape components and hierarchical skeletons from volume data are analyzed in this paper based on multiple distance transformations. The application of volume decomposition for the extraction of hierarchical skeletons is emphasized and specified here. This work includes an establishment of the hierarchical structure of the object volume, a decomposition of the volume into simple sub-volumes, an extraction of compact skeleton segments corresponding to each independent sub-volume, and a connection of these skeleton segments into a hierarchical structure reflecting the organization the initial data

Feature Detectors and Descriptors Generations With Numerous Images and Video Applications

2018 ◽  
pp. 571-600 ◽  
Author(s):  
Nilanjan Dey ◽  
Amira S. Ashour ◽  
Aboul Ella Hassanien
Keyword(s):  
Object Recognition ◽  
Video Retrieval ◽  
Critical Role ◽  
Medical Applications ◽  
Visual Feature ◽  
Interest Points ◽  
Feature Detectors ◽  
Computational Speed ◽  
Real Time Applications ◽  
Over Time

Feature detectors have a critical role in numerous applications such as camera calibrations, object recognition, biometrics, medical applications and image/video retrieval. One of its main tasks is to extract point correspondences “Interest points” between two similar scenes, objects, images or video shots. Extensive research has been done concerning the progress of visual feature detectors and descriptors to be robust against image deformations and achieve reduced computational speed in real-time applications. The current chapter introduced an overview of feature detectors such as Moravec, Hessian, Harris and FAST (Features from Accelerated Segment Test). It addressed the feature detectors' generation over time, the principle concept of each type, and their use in image/video applications. Furthermore, some recent feature detectors are addressed. A comparison based on these points is performed to illustrate their respective strengths and weaknesses to be a base for selecting an appropriate detector according to the application under concern.

Image Retrieval and Analysis Using Text and Fuzzy Shape Features

2018 ◽  
Author(s):  
P. Sumathy ◽  
P. Shanmugavadivu ◽  
A. Vadivel
Keyword(s):  
Image Retrieval ◽  
Shape Features

Using combination of color, texture, and shape features for image retrieval in melanomas databases

2001 ◽  
Author(s):  
Mohamed-Chaker Larabi ◽  
Noel Richard ◽  
Christine Fernandez-Maloigne
Keyword(s):  
Image Retrieval ◽  
Shape Features ◽  
Color Texture
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