Exploiting angular profiles signature for shape-based image classification and retrieval

  title={Exploiting angular profiles signature for shape-based image classification and retrieval},
  author={Jamil Ahmad and Khan Muhammad and Zahoor Jan},
  journal={Int. J. Appl. Pattern Recognit.},
Image classification and retrieval has significant importance in a wide variety of applications like object recognition, tracking, and content based retrieval, etc. Images usually consist of various objects which are segmented and then analysed for object-based classification and recognition. Owing to the absence of intensity and colour information, binary objects are difficult to recognise. They are usually represented using compact, geometrically invariant and robust features extracted from… 
Tamper Localization and Self-Recovery Scheme for Medical Image Analysis Using SVD-based Fragile Watermarking
SVD-based watermarking information improves the image authentication and provides a way to detect different attacked area and the proposed scheme is tested against different types of attacks such as text removal attack, text insertion attack, and copy and paste attack.


A New Shape Signature for Fourier Descriptors
This paper investigates the Fourier descriptor (FD) technique and presents a novel shape registration method for extracting Fourier descriptors, which exhibits superior performance against curvature scale space (CSS) and Zernike moments (ZM) in shape-based image retrieval.
A Fusion of Labeled-Grid Shape Descriptors with Weighted Ranking Algorithm for Shapes Recognition
The experimental analysis has shown that the proposed fusion based shapes recognition method is powerful enough to discriminate the geometrically similar shapes from the non-similar ones.
Shape matching and classification using height functions
Learning the shape manifold to improve object recognition
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.
Blurred Shape Model for binary and grey-level symbol recognition
Shape matching and object recognition using shape contexts
This paper presents work on computing shape models that are computationally fast and invariant basic transformations like translation, scaling and rotation, and proposes shape detection using a feature called shape context, which is descriptive of the shape of the object.
Study and evaluation of different Fourier methods for image retrieval
Robust symbolic representation for shape recognition and retrieval