Image Retrieval of Songket Motifs Using Simple Shape Descriptors

2006 ◽  
Author(s):  
N. Jamil ◽  
Z.A. Bakar ◽  
T.M. Tengku Sembok
Keyword(s):  
Image Retrieval ◽  
Shape Descriptors ◽  
Simple Shape

scholarly journals VOLUME ESTIMATION FROM SINGLE IMAGES: AN APPLICATION TO PANCREATIC ISLETS

2018 ◽  
Vol 37 (3) ◽  
pp. 191 ◽  
Author(s):  
Jiří Dvořák ◽  
Jan Švihlík ◽  
Jan Kybic ◽  
Barbora Radochová ◽  
Jiří Janáček ◽  
...  
Keyword(s):  
Volume Estimation ◽  
Estimation Methods ◽  
Particle Model ◽  
Shape Descriptors ◽  
Single Image ◽  
Simple Shape ◽  
Segmented Image ◽  
Image Volume ◽  
3D Shapes ◽  
Better Than

The present paper deals with the problem of volume estimation of individual objects from a single 2D view. Our main application is volume estimation of pancreatic (Langerhans) islets and the single 2D view constraint comes from the time and equipment limitations of the standard clinical procedure.Two main approaches are followed in this paper. First, two regression-based methods are proposed, using a set of simple shape descriptors of the segmented image of the islet. Second, two example-based methods are proposed, based on a database of islets with known volume. For training and evaluation, islet volumes were determined by OPT microscopy and a semi-automatical stereological volume estimation using the so-called Fakir probes.The performance of the single image volume estimation methods is studied on a set of 99 islets from human donors. Further experiments were also performed on a stone dataset and on synthetic 3D shapes, generated using a flexible stochastic particle model. The proposed methods are fast and the experimental results show that in most situations the proposed methods perform significantly better than the methods currently used in clinical practice, which are based on simple spherical or ellipsoidal models.

Alumina Sintering Kiln Flame Image Retrieval Based on ANN and Flame Shape Feature

2009 ◽  
Vol 4 (1) ◽  
Author(s):  
Hongliang Zhang ◽  
Jie Li ◽  
Zhong Zou
Keyword(s):  
Image Retrieval ◽  
Rotary Kiln ◽  
Shape Descriptor ◽  
High Accuracy ◽  
Retrieval Algorithm ◽  
Shape Descriptors ◽  
Shape Features ◽  
Retrieval Method ◽  
Flame Shape ◽  
Artificial Neural Network Ann

An alumina sintering rotary kiln flame image retrieval method was put forward based on artificial neural network (ANN) and flame shape features. An effective flame shape descriptor was introduced, based on which the flame image recognitions were carried out using ANN. Then, a flame image retrieval algorithm was designed. Experiments were carried out on the prototype machine with the flame images sampled from an alumina sintering rotary kiln. The results indicate that the shape descriptors can effectively describe the flame shapes and the proposed flame image retrieval method can achieve both high accuracy and efficiency. This method can be of promising theoretical and practical value for alumina sintering rotary kiln management and surveillance.

Evaluation of shape descriptors for shape-based image retrieval

2011 ◽  
Vol 5 (5) ◽  
pp. 493 ◽  
Author(s):  
A. Amanatiadis ◽  
V.G. Kaburlasos ◽  
A. Gasteratos ◽  
S.E. Papadakis
Keyword(s):  
Image Retrieval ◽  
Shape Descriptors

Comparison of Fourier and normal angle descriptors for the content-based image retrieval

2016 ◽  
Vol 83 (4) ◽  
Author(s):  
Pilar Hernández Mesa ◽  
Fernando Puente León
Keyword(s):  
Image Retrieval ◽  
Distance Functions ◽  
Content Based Image Retrieval ◽  
Fourier Descriptors ◽  
Shape Descriptors ◽  
Shape Information ◽  
Normal Vectors ◽  
Normal Angle

AbstractAppropriate methods are necessary to compare and search images automatically without using tags. In this work the retrieval of similar objects in images using the shape information is investigated. For this purpose, Fourier descriptors and the angles from the normal vectors along the boundaries of the objects are used as shape descriptors. Three different features are extracted from the Fourier descriptors to compare the objects. Three different distance functions are proposed to measure the similarity between the objects when the angles of the normal vectors are used as features. Finally, the appropriateness of these methods for the content-based image retrieval is compared at a commonly used database to test such cases.

Using Global Shape Descriptors for Content Medical-Based Image Retrieval

2013 ◽  
pp. 492-502
Author(s):  
Saïd Mahmoudi ◽  
Mohammed Benjelloun
Keyword(s):  
Fourier Transform ◽  
Image Retrieval ◽  
Real Time ◽  
Search Engine ◽  
Shape Descriptors ◽  
Query Image ◽  
Global Shape ◽  
Aided Diagnosis ◽  
Preliminary Classification

In this chapter, the authors propose a new method belonging to content medical-based image retrieval approaches and that uses a set of region-based shape descriptors. The search engine discussed in this work allows the classification of newly acquired medical images into some well known categories and also to get the images that are more similar to a query image. The final goal is to help the medical staff to annotate these images. To achieve this task, the authors propose a set of three descriptors that are based on: (1) Hu, (2) Zernike moments, and (3) Fourier transform-based signature, which are considered as region descriptors. The advantage of using this kind of global descriptor is that they are very fast, real time, and they do not need any segmentation step. The authors propose also a comparative study between these three approaches. The search engines are tested by using a database composed of 75 images that have different sizes, and that are classified into five classes. The results provided by the proposed retrieval approaches are given with high precision. The comparison between the three approaches is achieved using classification matrices and the recall/precision curves. The three proposed retrieval approaches produce accurate results in real time. This proves the advantage of using global shape features as a preliminary classification step in an automated aided diagnosis system.

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