scholarly journals An Automatic Localization Algorithm for Ultrasound Breast Tumors Based on Human Visual Mechanism

Sensors ◽  
2017 ◽  
Vol 17 (5) ◽  
pp. 1101 ◽  
Author(s):  
◽  
◽  
Keyword(s):  
Breast Tumors ◽  
Localization Algorithm ◽  
Visual Mechanism ◽  
Human Visual Mechanism ◽  
Automatic Localization

scholarly journals Automatic Localization Algorithm for Ultrasound Breast Tumors Based on Human Visual Mechanism

2017 ◽  
Author(s):  
Yuting Xie ◽  
Ke Chen ◽  
Jiangli Lin
Keyword(s):  
Level Set ◽  
Automatic Segmentation ◽  
Breast Tumors ◽  
Input Image ◽  
Object Localization ◽  
Initial Contour ◽  
Natural Image ◽  
Localization Algorithm ◽  
Localization Method ◽  
Automatic Localization

Human visual system (HVM) can quickly localize the most salient object in scenes, which has been widely applied on natural image segmentation [15]-[19]. In ultrasound (US) breast images, compared with background areas, tumor is more salient because of its higher contrast. In this paper, we develop a novel automatic localization method based on HVM for automatic segmentation of ultrasound (US) breast tumors. First, the input image is smoothed by convolution with a linearly separable Gaussian filter and then subsampled into a 9-layer Gaussian pyramid. Then intensity, blackness ratio, and superpixel contrast features are combined to compute saliency map, in which Winner Take All algorithm is used to localize the most salient region, presenting with a circle on the localized target. Finally the circle is taken as the initial contour of CV level set to finish the extraction of breast tumor. The localization method has been tested on 400 US beast images, among which 378 images have higher saliency than background areas and succeed in localization, with high accuracy 92.00%. The HVM localization method can be used to localize the tumors, combined with this method, CV level set can achieve the fully automatic segmentation of US breast tumors. By combing intensity, blackness ratio and superpixel contrast features, the proposed localization method can successfully avoid the interference caused by background areas with low echo and high intensity. Moreover, multi-object localization of US breast images can be considered in future employment.

Information Processing in Visual System - Optical Illusion and Visual Mechanism

2001 ◽  
Vol 13 (6) ◽  
pp. 569-574
Author(s):  
Masanori Idesawa ◽  
Keyword(s):  
Information Processing ◽  
Visual System ◽  
Visual Function ◽  
External World ◽  
Automated System ◽  
Human Beings ◽  
Optical Illusion ◽  
Optical Illusions ◽  
Visual Mechanism ◽  
Human Visual Mechanism

Human beings obtain big amount of information from the external world through their visual system. Automated system such as robot must provide the visual functions for their flexible operations in 3-D circumstances. In order to realize the visual function artificially, we would be better to learn from the human visual mechanism. Optical illusions would be a pure reflection of the human visual mechanism; they can be used for investigating human visual mechanism. New types of optical illusion with binocular viewing are introduced and investigated.

Research on Shape Feature Recognition of Boundary Representation CAD Model

2017 ◽  
Vol 14 (1) ◽  
pp. 477-484
Author(s):  
Jihua Wang
Keyword(s):  
Feature Recognition ◽  
Boundary Representation ◽  
Surface Boundary ◽  
Cad Model ◽  
Shape Feature ◽  
Product Model ◽  
Data Files ◽  
Visual Mechanism ◽  
Human Visual Mechanism ◽  
Visual Shape

B-Rep (Boundary Representation) CAD model is being widely used in representation of industrial product, so its feature recognition has acquired widespread research interests in computer vision and 3D model retrieval fields. We present one approach of feature recognition based on the idea of human visual mechanism. Surfaces as the visual shape features, and solids as well as shells as the topological relations, were extracted from the neutral STEP (Standard for Exchange of Product Model Data) files of B-Rep model. Towards three surface types of NURBS, analytical and poly loop, the properties of surface boundary and region are established based on curvature and other geometric index. So B-Rep CAD model is characterized as the hierarchical tree with solid layer, shell layer and surface layer for object recognition and retrieval, and the corresponding experiments verified the effectiveness of the method of shape feature recognition.

Automatic Localization Algorithm of Multiple Barcodes

2011 ◽  
Vol 317-319 ◽  
pp. 859-864
Author(s):  
Yin Hua Huang ◽  
Shi Qi Zhao
Keyword(s):  
Candidate Region ◽  
Experimental Results ◽  
Localization Algorithm ◽  
Key Technology ◽  
Complex Background ◽  
Blob Analysis ◽  
Barcode Recognition ◽  
Automatic Localization

Localization of barcode is the key technology for barcode recognition. This paper presents an automatic localization algorithm for multiple barcodes in complex background. The proposed algorithm includes dividing the image into a plurality of tiles, and scanning each of the tiles so as to detect a pattern of strips associated with the barcode in at least one of the tiles. The pattern of strips is analyzed so as to determine the candidate region. Then the effective affine region of barcode is computed by the method of Blob analysis and the barcode is only contained in it. Experimental results indicate that the proposed approach has certain accuracy, the efficiency and robustness.

Infrared Dim Target Detection Based on Human Visual Mechanism

2021 ◽  
Vol 50 (1) ◽  
pp. 173-187
Author(s):  
危水根 Shuigen WEI ◽  
王程伟 Chengwei WANG ◽  
陈震 Zhen CHEN ◽  
张聪炫 Congxuan ZHANG ◽  
张晓雨 Xiaoyu ZHANG
Keyword(s):  
Target Detection ◽  
Visual Mechanism ◽  
Human Visual Mechanism

3-D Computer Graphics System for Vision Research by Binocular Viewing

1992 ◽  
Vol 4 (1) ◽  
pp. 70-75
Author(s):  
Masanori Idesawa ◽  
◽  
Yasuhiro Mizukoshi ◽  
Keyword(s):  
Vision Research ◽  
Space Perception ◽  
Binocular Viewing ◽  
Stereoscopic Display ◽  
Time Sharing ◽  
Display System ◽  
Visual Mechanism ◽  
Human Visual Mechanism ◽  
Liquid Crystal Shutter ◽  
Computer Graphics System

For the artificial realization and the application of the visual function of 3-D space perception, the better understanding of human visual mechanism is required strongly. The disparity and occlusion observed with binocular viewing seems to be the most important cues to get 3-D information. Then, the authors developed a simple stereoscopic display system using a time sharing display of left eye and right eye images with liquid crystal shutter. This system is composed of a simple small control circuit and has big advantages such as that the hardware can be applied to any types of display system and the software can be transplant to different type computer system easily. Then, the authors tried to apply this system for the vision research of 3-D perceptural function with binocular viewing.

Infrared Dim Target Detection Based on Human Visual Mechanism

2021 ◽  
Vol 50 (1) ◽  
pp. 173-187
Author(s):  
危水根 Shuigen WEI ◽  
王程伟 Chengwei WANG ◽  
陈震 Zhen CHEN ◽  
张聪炫 Congxuan ZHANG ◽  
张晓雨 Xiaoyu ZHANG
Keyword(s):  
Target Detection ◽  
Visual Mechanism ◽  
Human Visual Mechanism

A Study on Visual Mechanism with Optical Illusions

1997 ◽  
Vol 9 (2) ◽  
pp. 85-91 ◽  
Author(s):  
Masanori Idesawa ◽  
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
Visual Stimuli ◽  
Close Relation ◽  
Depth Information ◽  
Optical Illusions ◽  
System A ◽  
Visual Mechanism ◽  
Human Visual Mechanism ◽  
Processing Techniques

Optical illusion seems to be the phenomena which are purely reflecting the mechanism of.human visual system and are expected as the effective cues to elucidating human visual mechanism. The author found the new types of 3-D visual illusion with binocular viewing. From the visual stimuli of binocular disparity given only along the contour of an object, human visual system can perceive entire 3-D illusory object where there are no physical visual stimuli giving depth information. They have close relation with the 3-D space perceiving functions in the human visual system. A study on these newly found optical illusions are introduced and the considerations are made for their applications and the exploitations including the contributions of information processing techniques such as computer graphics, computer vision and so on.

scholarly journals Face Manipulation Detection Based on Supervised Multi-Feature Fusion Attention Network

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8181
Author(s):  
Lin Cao ◽  
Wenjun Sheng ◽  
Fan Zhang ◽  
Kangning Du ◽  
Chong Fu ◽  
...  
Keyword(s):  
Feature Fusion ◽  
Accurate Method ◽  
Attention Network ◽  
The Public ◽  
Single Feature ◽  
Visual Mechanism ◽  
The Rich ◽  
Human Visual Mechanism ◽  
Manipulation Detection ◽  
Human Eyes

Nowadays, faces in videos can be easily replaced with the development of deep learning, and these manipulated videos are realistic and cannot be distinguished by human eyes. Some people maliciously use the technology to attack others, especially celebrities and politicians, causing destructive social impacts. Therefore, it is imperative to design an accurate method for detecting face manipulation. However, most of the existing methods adopt single convolutional neural network as the feature extraction module, causing the extracted features to be inconsistent with the human visual mechanism. Moreover, the rich details and semantic information cannot be reflected with single feature, limiting the detection performance. Therefore, this paper tackles the above problems by proposing a novel face manipulation detection method based on a supervised multi-feature fusion attention network (SMFAN). Specifically, the capsule network is used for face manipulation detection, and the SMFAN is added to the original capsule network to extract details of the fake face image. Further, the focal loss is used to realize hard example mining. Finally, the experimental results on the public dataset FaceForensics++ show that the proposed method has better performance.

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