scholarly journals Image Retrieval Using the Intensity Variation Descriptor

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Zhao Wei ◽  
Guang-Hai Liu
Keyword(s):  
Image Retrieval ◽  
Information Extraction ◽  
Lateral Inhibition ◽  
Intensity Variation ◽  
Spatial Layout ◽  
Inhibition Mechanism ◽  
Square Root ◽  
Optimal Direction ◽  
Selective Mechanism ◽  
Better Than

Variations between image pixel characteristics contain a wealth of information. Extraction of such cues can be used to describe image content. In this paper, we propose a novel descriptor, called the intensity variation descriptor (IVD), to represent variations in colour, edges, and intensity and apply it to image retrieval. The highlights of the proposed method are as follows. (1) The IVD combines the advantages of the HSV and RGB colour spaces. (2) It can simulate the lateral inhibition mechanism and orientation-selective mechanism to determine an optimal direction and spatial layout. (3) An extended weighted L1 distance metric is proposed to calculate the similarity of images. It does not require complex operations such as square or square root and leads to good performance. Comparative experiments on two Corel datasets containing 15,000 images show that the proposed method performs better than the SoC-GMM, CPV-THF, and STH methods and provides good matching of texture, colour, and shape.

Whale optimization algorithm based on lateral inhibition for image matching and vision-guided AUV docking

2020 ◽  
pp. 1-12
Author(s):  
Zheping Yan ◽  
Jinzhong Zhang ◽  
Jialing Tang
Keyword(s):  
Lateral Inhibition ◽  
Optimization Algorithm ◽  
Image Matching ◽  
Autonomous Underwater Vehicle ◽  
Optimal Solution ◽  
Search Space ◽  
Whale Optimization Algorithm ◽  
Inhibition Mechanism ◽  
Whale Optimization ◽  
Accuracy And Stability

The accuracy and stability of relative pose estimation of an autonomous underwater vehicle (AUV) and a target depend on whether the characteristics of the underwater image can be accurately and quickly extracted. In this paper, a whale optimization algorithm (WOA) based on lateral inhibition (LI) is proposed to solve the image matching and vision-guided AUV docking problem. The proposed method is named the LI-WOA. The WOA is motivated by the behavior of humpback whales, and it mainly imitates encircling prey, bubble-net attacking and searching for prey to obtain the globally optimal solution in the search space. The WOA not only balances exploration and exploitation but also has a faster convergence speed, higher calculation accuracy and stronger robustness than other approaches. The lateral inhibition mechanism can effectively perform image enhancement and image edge extraction to improve the accuracy and stability of image matching. The LI-WOA combines the optimization efficiency of the WOA and the matching accuracy of the LI mechanism to improve convergence accuracy and the correct matching rate. To verify its effectiveness and feasibility, the WOA is compared with other algorithms by maximizing the similarity between the original image and the template image. The experimental results show that the LI-WOA has a better average value, a higher correct rate, less execution time and stronger robustness than other algorithms. The LI-WOA is an effective and stable method for solving the image matching and vision-guided AUV docking problem.

The Experimental Study on the Inhibition Effect of Fusarium oxyspomm with Bio-Slurry Based on Material Properties

2013 ◽  
Vol 675 ◽  
pp. 317-321
Author(s):  
Meng Ying Fang ◽  
Li Chun Liu ◽  
Fang Yin ◽  
Wu Di Zhang ◽  
Shi Qing Liu ◽  
...  
Keyword(s):  
Experimental Study ◽  
Material Properties ◽  
Water Soluble ◽  
Inhibition Mechanism ◽  
Main Subject ◽  
Soluble Substance ◽  
Inhibition Effect ◽  
Water Soluble Substance ◽  
Main Component ◽  
Better Than

Using petroleum ether to extract the fermentative fluid (bio-slurry), then to get the inhibition mechanism of it, and infer which is the main component in inhibition mechanism of biogas. The conclusion found by the experiment is that fat soluble substance is better than water soluble substance in inhibition mechanism, and fat soluble substance is close to 75% biogas fermentation fluid, while water soluble substance is worst. That is to say, the main subject in inhibition mechanism is hided in the fat soluble substance.

Shape and spatial color information extraction for image retrieval

2001 ◽  
Author(s):  
Panagiotis Androutsos ◽  
Diana Ferrari ◽  
Allen Ly ◽  
Andrew Persaud ◽  
Dimitrios Androutsos ◽  
...  
Keyword(s):  
Image Retrieval ◽  
Information Extraction ◽  
Color Information

Combining Block DCV and Support Vector Machine for Ear Recognition

2016 ◽  
Vol 8 (2) ◽  
pp. 36-44 ◽  
Author(s):  
Zhao Hailong ◽  
Yi Junyan
Keyword(s):  
Support Vector Machine ◽  
Feature Extraction ◽  
Image Retrieval ◽  
Construction Method ◽  
Experimental Results ◽  
Support Vector ◽  
Recognition Method ◽  
Ear Recognition ◽  
Human Ear ◽  
Better Than

In recent years, automatic ear recognition has become a popular research. Effective feature extraction is one of the most important steps in Content-based ear image retrieval applications. In this paper, the authors proposed a new vectors construction method for ear retrieval based on Block Discriminative Common Vector. According to this method, the ear image is divided into 16 blocks firstly and the features are extracted by applying DCV to the sub-images. Furthermore, Support Vector Machine is used as classifier to make decision. The experimental results show that the proposed method performs better than classical PCA+LDA, so it is an effective human ear recognition method.

scholarly journals Ptf1a control of Dll1 reveals an alternative to the lateral inhibition mechanism

Development ◽  
2012 ◽  
Vol 139 (23) ◽  
pp. 4492-4492 ◽  
Author(s):  
J. Ahnfelt-Ronne ◽  
M. C. Jorgensen ◽  
R. Klinck ◽  
J. N. Jensen ◽  
E.-M. Fuchtbauer ◽  
...  
Keyword(s):  
Lateral Inhibition ◽  
Inhibition Mechanism

scholarly journals Stochastic Fractal Search Algorithm for Template Matching with Lateral Inhibition

2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Qifang Luo ◽  
Sen Zhang ◽  
Yongquan Zhou
Keyword(s):  
Lateral Inhibition ◽  
Template Matching ◽  
Search Algorithm ◽  
Inhibition Mechanism ◽  
Edge Extraction ◽  
Matching Problems ◽  
Matching Technique ◽  
Image Edge ◽  
Stochastic Fractal Search Algorithm ◽  
Stochastic Fractal Search

Template matching is a basic and crucial process for image processing. In this paper, a hybrid method of stochastic fractal search (SFS) and lateral inhibition (LI) is proposed to solve complicated template matching problems. The proposed template matching technique is called LI-SFS. SFS is a new metaheuristic algorithm inspired by random fractals. Furthermore, lateral inhibition mechanism has been verified to have good effects on image edge extraction and image enhancement. In this work, lateral inhibition is employed for image preprocessing. LI-SFS takes both the advantages of SFS and lateral inhibition which leads to better performance. Our simulation results show that LI-SFS is more effective and robust for this template matching mission than other algorithms based on LI.

The Technique of Shape-Based Multi-Feature Combination of TradeMark Image Retrieval

2012 ◽  
Vol 429 ◽  
pp. 287-291 ◽  
Author(s):  
Cong Zhang ◽  
Fu Cheng You
Keyword(s):  
Image Retrieval ◽  
Euclidean Distance ◽  
Feature Matching ◽  
Region Growing ◽  
Local Information ◽  
Feature Combination ◽  
Single Feature ◽  
Hu Moments ◽  
Global Matching ◽  
Better Than

At present, the technique of trademark image retrieval based on multi-feature combination of the shape mainly includes single-feature global matching or local matching and multi-feature matching, which is playing a more and more important role in the area of the trademark image retrieval. In this paper, due to the deficiency described by some single shape-based features, the technique of the multi-feature combination trademark image retrieval is proposed based on the region and the edge of a shape. Firstly, a trademark image is segmented with region growing, then low order Hu moments and eccentricity are extracted on the resulting region, which is able to express the local information of the image; Secondly, there is an extraction of Compactness and Convexity, which describe the global feature of the image, on the edge extracted with Canny. At last, the combination of the multi-feature is applied to get a Euclidean distance. Good results have been obtained in the following experiment, which proves the multi-feature combination way is better than other single-feature ways.

scholarly journals Content-Based Image Retrieval Using Spatial Layout Information in Brain Tumor T1-Weighted Contrast-Enhanced MR Images

PLoS ONE ◽  
2014 ◽  
Vol 9 (7) ◽  
pp. e102754 ◽  
Author(s):  
Meiyan Huang ◽  
Wei Yang ◽  
Yao Wu ◽  
Jun Jiang ◽  
Yang Gao ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Image Retrieval ◽  
Spatial Layout ◽  
Content Based Image Retrieval ◽  
Mr Images ◽  
Contrast Enhanced
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