scholarly journals A Radiomic feature–based Nipple Detection Algorithm on Digital Mammography

2019 ◽  
Vol 46 (10) ◽  
pp. 4381-4391 ◽  
Author(s):  
Jiayu Jiang ◽  
Yaqin Zhang ◽  
Yao Lu ◽  
Yanhui Guo ◽  
Haibin Chen
Keyword(s):  
Digital Mammography ◽  
Detection Algorithm ◽  
Feature Based ◽  
Nipple Detection

Algorithm of Lane Detection on an Appropriate Limited Region

2013 ◽  
Vol 433-435 ◽  
pp. 267-272
Author(s):  
Xing Ma ◽  
Chun Yang Mu ◽  
Chun Tao Zhang ◽  
Lu Ming Zhang
Keyword(s):  
Urban Environment ◽  
Hough Transform ◽  
Region Of Interest ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Limited Region ◽  
Feature Based

This paper proposed a lane detection algorithm for urban environment. The algorithm was concerned on selecting an appropriate limited region of interest (ROI) by OTSU segmentation. Then candidates of lane markers were extracted by Canny, finally the lane boundaries were detected by Hough transform. The limited ROI helps to identification lane in an appropriate region. This process have the effect of enhancement in the speed of operation. The proposed algorithm was simulated in MATLAB. The test databases were shared by Fondazione Bruno Kessler (FBK). The experiments show that lane boundaries can be detected correctly although they are fade. Feature-based method is usually affected by intension of image. Several characteristics of roads need to be considered further for detection more precisely.

scholarly journals SIFT Feature-Based Video Camera Boundary Detection Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lingqiang Kong
Keyword(s):  
Complex Structure ◽  
Boundary Detection ◽  
Recall Rate ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Gradual Change ◽  
Dynamic Texture ◽  
Sift Feature ◽  
Film And Television ◽  
Feature Based

Aiming at the problem of low accuracy of edge detection of the film and television lens, a new SIFT feature-based camera detection algorithm was proposed. Firstly, multiple frames of images are read in time sequence and converted into grayscale images. The frame image is further divided into blocks, and the average gradient of each block is calculated to construct the film dynamic texture. The correlation of the dynamic texture of adjacent frames and the matching degree of SIFT features of two frames were compared, and the predetection results were obtained according to the matching results. Next, compared with the next frame of the dynamic texture and SIFT feature whose step size is lower than the human eye refresh frequency, the final result is obtained. Through experiments on multiple groups of different types of film and television data, high recall rate and accuracy rate can be obtained. The algorithm in this paper can detect the gradual change lens with the complex structure and obtain high detection accuracy and recall rate. A lens boundary detection algorithm based on fuzzy clustering is realized. The algorithm can detect sudden changes/gradual changes of the lens at the same time without setting a threshold. It can effectively reduce the factors that affect lens detection, such as flash, movies, TV, and advertisements, and can reduce the influence of camera movement on the boundaries of movies and TVs. However, due to the complexity of film and television, there are still some missing and false detections in this algorithm, which need further study.

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