Hybrid Method for Vehicle Detection from CCTV Captured Image

2013 ◽  
Vol 677 ◽  
pp. 412-417
Author(s):  
Suppatoomsin Chompoo ◽  
Srikaew Arthit
Keyword(s):  
Hybrid Method ◽  
Color Image ◽  
Principal Component ◽  
Vehicle Detection ◽  
Self Organizing Map ◽  
Resonance Theory ◽  
Difference Image ◽  
Fuzzy Art ◽  
Image Area ◽  
The Difference

This paper presents a hybrid method for vehicle detection from CCTV captured image. In order to overwhelm such complex details of the color image, the system combines artificial intelligence techniques to achieve automatic vehicle detection. These are techniques 2D principal component analysis (2DPCA), Fuzzy adaptive resonance theory (Fuzzy ART), genetic algorithm (GA) and self-organizing map. The proposed system can detect different vehicle sizes from different proportional image area. Bilinear interpolation is used to resize each proportional image area to vehicle feature matrix. The proposed system can detect various types of vehicles from the difference image background.

scholarly journals Rapid Disaster Analysis based on SAR Techniques

2015 ◽  
Vol XL-3/W2 ◽  
pp. 281-288
Author(s):  
C. H. Yang ◽  
U. Soergel
Keyword(s):  
Change Detection ◽  
Color Image ◽  
Complex Case ◽  
False Alarms ◽  
The 2011 Tohoku Earthquake ◽  
Detection Techniques ◽  
Linear Feature ◽  
Difference Image ◽  
The Difference ◽  
Flooded Area

Due to all-day and all-weather capability spaceborne SAR is a valuable means for rapid mapping during and after disaster. In this paper, three change detection techniques based on SAR data are discussed: (1) initial coarse change detection, (2) flooded area detection, and (3) linear-feature change detection. The 2011 Tohoku Earthquake and Tsunami is used as case study, where earthquake and tsunami events provide a complex case for this study. In (1), pre- and post-event TerraSAR-X images are coregistered accurately to produce a false-color image. Such image provides a quick and rough overview of potential changes, which is useful for initial decision making and identifies areas worthwhile to be analysed further in more depth. In (2), the post-event TerraSAR-X image is used to extract the flooded area by morphological approaches. In (3), we are interested in detecting changes of linear shape as indicator for modified man-made objects. Morphological approaches, e.g. thresholding, simply extract pixel-based changes in the difference image. However, in this manner many irrelevant changes are highlighted, too (e.g., farming activity, speckle). In this study, Curvelet filtering is applied in the difference image not only to suppress false alarms but also to enhance the change signals of linear-feature form (e.g. buildings) in settlements. Afterwards, thresholding is conducted to extract linear-shaped changed areas. These three techniques mentioned above are designed to be simple and applicable in timely disaster analysis. They are all validated by comparing with the change map produced by Center for Satellite Based Crisis Information, DLR.

A Novel Fault Diagnosis Method Using PCA and ART-Similarity Classifier Based on Yu’s Norm

2009 ◽  
Vol 413-414 ◽  
pp. 569-574 ◽  
Author(s):  
Zeng Bing Xu ◽  
Jian Ping Xuan ◽  
Tie Lin Shi ◽  
Bo Wu ◽  
You Min Hu
Keyword(s):  
Fault Diagnosis ◽  
Rbf Neural Network ◽  
Principal Component ◽  
Feature Maps ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Fuzzy Art ◽  
Comparison Results ◽  
Rolling Element ◽  
Diagnosis Method

In this paper, a novel similarity classifier which synthesizes the adaptive resonance theory (ART) and the similarity classifier based on the Yu’s norm is proposed. The proposed ART-similarity classifier can not only carry out training without forgetting previously trained patterns but also be adaptive to changes in the environment. In order to test the proposed classifier, it is applied to the fault diagnosis of rolling element bearings. Before application to the fault diagnosis of bearings, considering computation burden principal component analysis (PCA) is proposed to reduce the number of features. The PCs are input the proposed classifier to diagnose the faulty bearings. The experiment results testify that the proposed classifier can identify the faults accurately. Furthermore, in order to validate the effectiveness of the proposed classifier further, it compares with other neural networks, such as the fuzzy ART, self-organising feature maps (SOFMs) and radial basis function (RBF) neural network through diagnosing the bearings under the same conditions. The comparison results confirm the superiority of the proposed method.

Multivariate micropollutants analysis in marine waters

1995 ◽  
Vol 32 (9-10) ◽  
pp. 341-348
Author(s):  
V. Librando ◽  
G. Magazzù ◽  
A. Puglisi
Keyword(s):  
Multivariate Data Analysis ◽  
Partial Least Squares Regression ◽  
Environmental Chemistry ◽  
Sampling Site ◽  
Principal Component ◽  
Least Squares Regression ◽  
Organic Micropollutants ◽  
Suspended Material ◽  
The Difference

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a function of time. In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of organic micropollutants, particularly since some are known to be carcinogenic. As the number of measured parameters increases examining the data and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Multivariate Data Analysis (MVDA), Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR). The use of the first technique in this work has been applied to the interpretation of the quality of Augusta bay, by measuring the concentration of numerous organic micropollutants, together with the classical water pollution parameters, in different sites and at different times. The MVDA has highlighted the difference between various sampling sites whose data were initially thought to be similar. Furthermore, it has allowed a choice of more significant parameters for future monitoring and more suitable sampling site locations.

scholarly journals Distribution and Severity of Placental Lesions Caused by the Chlamydia abortus 1B Vaccine Strain in Vaccinated Ewes

Pathogens ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 543
Author(s):  
Sergio Gastón Caspe ◽  
Javier Palarea-Albaladejo ◽  
Clare Underwood ◽  
Morag Livingstone ◽  
Sean Ranjan Wattegedera ◽  
...  
Keyword(s):  
Disease Outbreaks ◽  
Principal Component ◽  
Placental Pathology ◽  
Wild Type ◽  
Cell Infiltrate ◽  
Chlamydia Abortus ◽  
Vaccine Type ◽  
The Difference ◽  
Enzootic Abortion Of Ewes

Chlamydia abortus infects livestock species worldwide and is the cause of enzootic abortion of ewes (EAE). In Europe, control of the disease is achieved using a live vaccine based on C. abortus 1B strain. Although the vaccine has been useful for controlling disease outbreaks, abortion events due to the vaccine have been reported. Recently, placental pathology resulting from a vaccine type strain (vt) infection has been reported and shown to be similar to that resulting from a natural wild-type (wt) infection. The aim of this study was to extend these observations by comparing the distribution and severity of the lesions, the composition of the predominating cell infiltrate, the amount of bacteria present and the role of the blood supply in infection. A novel system for grading the histological and pathological features present was developed and the resulting multi-parameter data were statistically transformed for exploration and visualisation through a tailored principal component analysis (PCA) to evaluate the difference between them. The analysis provided no evidence of meaningful differences between vt and wt strains in terms of the measured pathological parameters. The study also contributes a novel methodology for analysing the progression of infection in the placenta for other abortifacient pathogens.

scholarly journals Possibility of Human Gender Recognition Using Raman Spectra of Teeth

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3983
Author(s):  
Ozren Gamulin ◽  
Marko Škrabić ◽  
Kristina Serec ◽  
Matej Par ◽  
Marija Baković ◽  
...  
Keyword(s):  
Raman Spectra ◽  
Principal Component ◽  
Support Vector ◽  
Gender Recognition ◽  
Proof Of Concept ◽  
Male And Female ◽  
Tooth Type ◽  
Tooth Apex ◽  
The Difference

Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof-of-concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigated. Raman spectra were recorded from male and female molars and premolars on two distinct sites, tooth apex and anatomical neck. Recorded spectra were sorted into suitable datasets and initially analyzed with principal component analysis, which showed a distinction between spectra of male and female teeth. Then, reduced datasets with scores of the first 20 principal components were formed and two classification algorithms, support vector machine and artificial neural networks, were applied to form classification models for gender recognition. The obtained results showed that gender recognition with Raman spectra of teeth is possible but strongly depends both on the tooth type and spectrum recording site. The difference in classification accuracy between different tooth types and recording sites are discussed in terms of the molecular structure difference caused by the influence of masticatory loading or gender-dependent life events.

scholarly journals Changes in Phenols, Polysaccharides and Volatile Profiles of Noni (Morinda citrifolia L.) Juice during Fermentation

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2604
Author(s):  
Zhulin Wang ◽  
Rong Dou ◽  
Ruili Yang ◽  
Kun Cai ◽  
Congfa Li ◽  
...  
Keyword(s):  
Octanoic Acid ◽  
Solid Phase ◽  
Principal Component ◽  
Hexanoic Acid ◽  
Morinda Citrifolia ◽  
Gas Chromatography Mass Spectrometry ◽  
Aroma Characteristics ◽  
Volatile Profiles ◽  
The Difference ◽  
Aroma Components

The change in phenols, polysaccharides and volatile profiles of noni juice from laboratory- and factory-scale fermentation was analyzed during a 63-day fermentation process. The phenol and polysaccharide contents and aroma characteristics clearly changed according to fermentation scale and time conditions. The flavonoid content in noni juice gradually increased with fermentation. Seventy-three volatile compounds were identified by solid-phase microextraction coupled with gas chromatography–mass spectrometry (SPME-GC-MS). Methyl hexanoate, 3-methyl-3-buten-1-ol, octanoic acid, hexanoic acid and 2-heptanone were found to be the main aroma components of fresh and fermented noni juice. A decrease in octanoic acid and hexanoic acid contents resulted in the less pungent aroma in noni juice from factory-scale fermentation. The results of principal component analysis of the electronic nose suggested that the difference in nitrogen oxide, alkanes, alcohols, and aromatic and sulfur compounds, contributed to the discrimination of noni juice from different fermentation times and scales.

scholarly journals Global metabolomic and lipidomic analysis reveals the potential mechanisms of hemolysis effect of Ophiopogonin D and Ophiopogonin D' in vivo

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Huan-Hua Xu ◽  
Zhen-Hong Jiang ◽  
Cong-Shu Huang ◽  
Yu-Ting Sun ◽  
Long-Long Xu ◽  
...  
Keyword(s):  
Chemical Properties ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Practical Significance ◽  
Plasma Metabolites ◽  
Active Components ◽  
The Difference

Abstract Background OPD and OPD' are the two main active components of Ophiopogon japonicas in Shenmai injection (SMI). Being isomers of each other, they are supposed to have similar pharmacological activities, but the actual situation is complicated. The difference of hemolytic behavior between OPD and OPD' in vivo and in vitro was discovered and reported by our group for the first time. In vitro, only OPD' showed hemolysis reaction, while in vivo, both OPD and OPD' caused hemolysis. In vitro, the primary cause of hemolysis has been confirmed to be related to the difference between physical and chemical properties of OPD and OPD'. In vivo, although there is a possible explanation for this phenomenon, the one is that OPD is bio-transformed into OPD' or its analogues in vivo, the other one is that both OPD and OPD' were metabolized into more activated forms for hemolysis. However, the mechanism of hemolysis in vivo is still unclear, especially the existing literature are still difficult to explain why OPD shows the inconsistent hemolysis behavior in vivo and in vitro. Therefore, the study of hemolysis of OPD and OPD' in vivo is of great practical significance in response to the increase of adverse events of SMI. Methods Aiming at the hemolysis in vivo, this manuscript adopted untargeted metabolomics and lipidomics technology to preliminarily explore the changes of plasma metabolites and lipids of OPD- and OPD'-treated rats. Metabolomics and lipidomics analyses were performed on ultra-high performance liquid chromatography (UPLC) system tandem with different mass spectrometers (MS) and different columns respectively. Multivariate statistical approaches such as principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) were applied to screen the differential metabolites and lipids. Results Both OPD and OPD' groups experienced hemolysis, Changes in endogenous differential metabolites and differential lipids, enrichment of differential metabolic pathways, and correlation analysis of differential metabolites and lipids all indicated that the causes of hemolysis by OPD and OPD' were closely related to the interference of phospholipid metabolism. Conclusions This study provided a comprehensive description of metabolomics and lipidomics changes between OPD- and OPD'-treated rats, it would add to the knowledge base of the field, which also provided scientific guidance for the subsequent mechanism research. However, the underlying mechanism require further research.

scholarly journals A Novel Active Contours Model for Environmental Change Detection from Multitemporal Synthetic Aperture Radar Images

2020 ◽  
Vol 12 (11) ◽  
pp. 1746
Author(s):  
Salman Ahmadi ◽  
Saeid Homayouni
Keyword(s):  
Synthetic Aperture Radar ◽  
Change Detection ◽  
Active Contours ◽  
Training Data ◽  
Synthetic Aperture ◽  
Data Sets ◽  
Difference Image ◽  
Proposed Model ◽  
The Difference ◽  
Aperture Radar

In this paper, we propose a novel approach based on the active contours model for change detection from synthetic aperture radar (SAR) images. In order to increase the accuracy of the proposed approach, a new operator was introduced to generate a difference image from the before and after change images. Then, a new model of active contours was developed for accurately detecting changed regions from the difference image. The proposed model extracts the changed areas as a target feature from the difference image based on training data from changed and unchanged regions. In this research, we used the Otsu histogram thresholding method to produce the training data automatically. In addition, the training data were updated in the process of minimizing the energy function of the model. To evaluate the accuracy of the model, we applied the proposed method to three benchmark SAR data sets. The proposed model obtains 84.65%, 87.07%, and 96.26% of the Kappa coefficient for Yellow River Estuary, Bern, and Ottawa sample data sets, respectively. These results demonstrated the effectiveness of the proposed approach compared to other methods. Another advantage of the proposed model is its high speed in comparison to the conventional methods.

The Design of Real-Time Face Detection System Based on FPGA

2013 ◽  
Vol 473 ◽  
pp. 231-234
Author(s):  
Su Hua Chen ◽  
Xu Fang ◽  
Yong Guang Liu ◽  
Jun Wang
Keyword(s):  
Processing Speed ◽  
Detection System ◽  
Main Body ◽  
Infrared Source ◽  
Difference Image ◽  
Small Influence ◽  
The Face ◽  
The Difference ◽  
Locating System ◽  
Image Difference

The design attempts for thefirst time to realize face locating system on the FPGA platform using themethod combined initiative infrared source with image difference. Through imagedifference process, the system obtains a difference image without backgroundinterference which takes the face as the main body. It can obtain the personface boundary by projecting the difference image in the horizontal and verticaldirection. The system processing speed amount s to the video source frequency25 frame per second, satisfying the timely request; the method of initiativeinfrared source makes the exterior have small influence on the image andguarantees the robustness of the system.

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