Edge extraction method for medical images based on improved local binary pattern combined with edge-aware filtering

2022 ◽  
Vol 74 ◽  
pp. 103490
Author(s):  
Shuang Qiao ◽  
Qinghan Yu ◽  
Zhengwei Zhao ◽  
Liying Song ◽  
Hui Tao ◽  
...  
2020 ◽  
Vol 7 (4) ◽  
pp. 79-86
Author(s):  
Nagadevi Darapureddy ◽  
Nagaprakash Karatapu ◽  
Tirumala Krishna Battula

This paper examines a hybrid pattern i.e. Local derivative Vector pattern and comparasion of this pattern over other different patterns for content-based medical image retrieval. In recent years Pattern-based texture analysis has significant popularity for a variety of tasks like image recognition, image and texture classification, and object detection, etc. In literature, different patterns exist for texture analysis. This paper aims at forming a hybrid pattern compared in terms of precision, recall and F1-score with different patterns like Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Completed Local Binary Pattern (CLBP), Local Tetra Pattern (LTrP), Local Vector Pattern (LVP) and Local Anisotropic Pattern (LAP) which were applied on medical images for image retrieval. The proposed method is evaluated on different modalities of medical images. The results of the proposed hybrid pattern show biased performance compared to the state-of-the-art. So this can further extended with other pattern to form a hybrid pattern.


2010 ◽  
Vol 39 (4) ◽  
pp. 759-763
Author(s):  
陈亮 CHEN Liang ◽  
郭雷 GUO Lei

2013 ◽  
Vol 427-429 ◽  
pp. 1874-1878
Author(s):  
Guo De Wang ◽  
Zhi Sheng Jing ◽  
Guo Wei Qin ◽  
Shan Chao Tu

Wear particles recognition is a key link in the process of Ferrography analysis. Different kinds of wear particles vary greatly in texture, texture feature is one of the most important feature in wear particles recognition. Local Binary Pattern (LBP) is an efficient operator for texture description. The binary sequence of traditional LBP operator is obtained by the comparison between the gray value of the neighborhood and the gray value of the center pixel of the neighborhood, the comparison is too simple to cause the loss of the texture. In this paper, an improved LBP operator is presented for texture feature extraction and it is applied to the recognition of severe sliding particles, fatigue spall particles and laminar particles. The experimental results show that our method is an effective feature extraction method and obtains better recognition accuracy compared with other methods.


2014 ◽  
Vol 687-691 ◽  
pp. 3765-3768
Author(s):  
Nan Wang

A new edge extraction method was put forward based on the SUSAN operator, according to the problems of poor anti-noise ability and edge detection incomplete of the conventional differential detection operator. The circular template and the center of the circle (template nuclear) were used in this method, the numbers of pixels was calculated through the comparison pixels value of template with the other points of pixels in the template circle, and then compared with the threshold, so as to the edge of images was extracted. The results showed that this method had high precision, and could be able to fully extract the edge of images. It is an effective method of extracting the edge of images.


2020 ◽  
Vol 10 (6) ◽  
pp. 1288-1293
Author(s):  
K. N. Madhusudhan ◽  
P. Sakthivel

The image authentication is generally based on two different types of techniques: watermarking and digital signature. In watermarking methods, embedded watermarking is often imperceptible and it contains either a specific ID of producer or codes related to content that are used for authentication. Normally a separate file is stored, digital signature is a non-repudiation and encrypted version of the information extracted from the data. A digital signature can be attached to the data to prove the originality and integrity. The proposed work presents a new approach to steganography of medical images that uses modified Least Significant Bit (LSB) based on the Local Binary Pattern (LBP) pattern. As a first step, cover image has been divided as blocks of 3×3 non overlapping masks. Then, the pixel embedding position (clock wise or anti-clock wise) has to be identified using LBP operator. The value of the LBP operator determines how and where to embed secret image pixel. Later, using LSB method, pixel values will be embedded in the cover image pixel. In order to provide the integrity of the data, the proposed work also presents Reversible Watermarking (RW), a Digital Signature (DS) technique. The proposed algorithm of steganography experimented on few medical images and achieved better efficiency with respect to MSE and PSNR values and same is reported in this paper.


2014 ◽  
Vol 568-570 ◽  
pp. 668-671
Author(s):  
Yi Long ◽  
Fu Rong Liu ◽  
Guo Qing Qiu

To address the problem that the dimension of the feature vector extracted by Local Binary Pattern (LBP) for face recognition is too high and Principal Component Analysis (PCA) extract features are not the best classification features, an efficient feature extraction method using LBP, PCA and Maximum scatter difference (MSD) has been introduced in this paper. The original face image is firstly divided into sub-images, then the LBP operator is applied to extract the histogram feature. and the feature dimensions are further reduced by using PCA. Finally,MSD is performed on the reduced PCA-based feature.The experimental results on ORL and Yale database demonstrate that the proposed method can classify more effectively and can get higher recognition rate than the traditional recognition methods.


2008 ◽  
Vol 16 (1) ◽  
Author(s):  
A. Walczak ◽  
L. Puzio

AbstractThe novel two-dimensional (2D) wavelet with anisotropic property and application of it has been presented. Wavelet is constructed in the polar coordinate system to obtain anisotropic properties. A novel edge detection method has been developed with the aid of this wavelet. This method detects gradient jump and than follows along this jump. In this way the number of calculation for edge localization is reduced. Moreover, the presented method is able to detect all edges in an image in multi-scale together with its spatial orientation. Proposed wavelet as well as edge extraction method seems to be new way to edge detection for an image.


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