The Research and Exploration of Soft X-Ray Microscopy on the Image Identification System of Squamocellular Cancer of Esophagus

2010 ◽  
Author(s):  
Jian Hao ◽  
Fan Zhang
Keyword(s):  
Identification System ◽  
Image Identification ◽  
X Ray

Qualitative phase analysis system for crystalline mixtures based on X-ray powder diffraction file

2004 ◽  
Vol 19 (4) ◽  
pp. 340-346
Author(s):  
YuanYuan Qiao ◽  
YunFei Xi ◽  
DongTao Zhuo ◽  
Ji Jun Wang ◽  
ShaoFan Lin
Keyword(s):  
Phase Analysis ◽  
Powder Diffraction ◽  
Identification System ◽  
Phase Identification ◽  
Powder Diffraction File ◽  
X Ray ◽  
Analysis System ◽  
Qualitative Phase ◽  
Full Peak

A qualitative phase identification system for crystalline mixtures is presented. The system provides up to five-phase qualitative identification using up to nine-peak filtration, and additive full peak matching based on the powder diffraction file of ICDD. It was implemented using Microsoft Visual C++, and runs under most common Windows systems. Screenshots and examples are included.

Newly Automated EPMA with Phase Identification System

2001 ◽  
Vol 7 (S2) ◽  
pp. 980-981
Author(s):  
S. Notoya ◽  
H. Takahashi ◽  
T. Okumura ◽  
C.H. Nielsen
Keyword(s):  
High Resolution ◽  
Optical Microscope ◽  
Image Display ◽  
Identification System ◽  
Phase Identification ◽  
Analysis Software ◽  
X Ray ◽  
Electron Probe Microanalyzer ◽  
Mouse Pointer ◽  
Live Image

We have developed a new Electron Probe Microanalyzer (EPMA), JXA-8100/8200, with improved basic capabilities such as X-ray intensities of wavelength dispersive spectrometers (WDS), imaging functions, automated functions and analysis software. Fig. 1 shows the appearance of JXA-8200, WD/ED combined microanalyzer. in this session, we report mainly on the improved imaging functions, automated functions and analysis software.The JXA-8100/8200 is the first EPMA in the world to feature 1280 x 1024 pixels high resolution live scanning image display. Regarding scanning image, two or four different signal live images, of course including X-ray images, can be displayed simultaneously. Further, image mixing is also possible to display. On the high resolution image, an operator can choose the probe position or the stage position by mouse clicking. The stage position can also be chosen on the optical microscope (OM) live image. Another new “Swing Mouse” function, which is the seamless movement of mouse pointer between the scanning image display and the computer display, has been developed.Advanced automated functions, such as autofocus, auto astigmatism and auto contrast brightness, are effective to optimize the scanning image.

Automating Human Identification Using Dental X-Ray Radiographs

2011 ◽  
pp. 280-314
Author(s):  
Omaima Nomir ◽  
Mohamed Abdel Mottaleb
Keyword(s):  
Field Energy ◽  
Identification System ◽  
Fourier Descriptors ◽  
X Ray ◽  
Advantages And Disadvantages ◽  
The Third ◽  
Salient Points ◽  
Chamfer Distance ◽  
Overall Performance ◽  
Matching Techniques

The goal of forensic dentistry is to identify individuals based on their dental characteristics. This chapter presents a system for automating that process by identifying people from dental X-ray images. Given a dental image of a postmortem (PM), the proposed system retrieves the best matches from an antemortem (AM) database. The system automatically segments dental X-ray images into individual teeth and extracts representative feature vectors for each tooth, which are later used for retrieval. This chapter details a new method for teeth segmentation, and three different methods for representing and matching teeth. Each method has a different technique for representing the tooth shape and has its advantages and disadvantages compared with the other methods. The first method represents each tooth contour by signature vectors obtained at salient points on the contour of the tooth. The second method uses Hierarchical Chamfer distance for matching AM and PM teeth. In the third method, each tooth is described using a feature vector extracted using the force field energy function and Fourier descriptors. During retrieval, according to a matching distance between the AM and PM teeth, AM radiographs that are most similar to a given PM image, are found and presented to the user. To increase the accuracy of the identification process, the three matching techniques are fused together. The fusion of information is an integral part of any identification system to improve the overall performance. This chapter introduces some scenarios for fusing the three matchers at the score level as well as at the fusion level.

Validating an automated image identification process of a passive image-assisted dietary assessment method: proof of concept

2020 ◽  
Vol 23 (15) ◽  
pp. 2700-2710
Author(s):  
Tsz-Kiu Chui ◽  
Jindong Tan ◽  
Yan Li ◽  
Hollie A. Raynor
Keyword(s):  
Dietary Assessment ◽  
False Negative ◽  
Assessment Method ◽  
Identification Accuracy ◽  
Identification System ◽  
True Negative ◽  
Image Identification ◽  
Effect Of Food ◽  
Food Image ◽  
Food Images

AbstractObjective:To validate an automated food image identification system, DietCam, which has not been validated, in identifying foods with different shapes and complexities from passively taken digital images.Design:Participants wore Sony SmartEyeglass that automatically took three images per second, while two meals containing four foods, representing regular- (i.e., cookies) and irregular-shaped (i.e., chips) foods and single (i.e., grapes) and complex (i.e., chicken and rice) foods, were consumed. Non-blurry images from the meals’ first 5 min were coded by human raters and compared with DietCam results. Comparisons produced four outcomes: true positive (rater/DietCam reports yes for food), false positive (rater reports no food; DietCam reports food), true negative (rater/DietCam reports no food) or false negative (rater reports food; DietCam reports no food).Setting:Laboratory meal.Participants:Thirty men and women (25·1 ± 6·6 years, 22·7 ± 1·6 kg/m2, 46·7 % White).Results:Identification accuracy was 81·2 and 79·7 % in meals A and B, respectively (food and non-food images) and 78·7 and 77·5 % in meals A and B, respectively (food images only). For food images only, no effect of food shape or complexity was found. When different types of images, such as 100 % food in the image and on the plate, <100 % food in the image and on the plate and food not on the plate, were analysed separately, images with food on the plate had a slightly higher accuracy.Conclusions:DietCam shows promise in automated food image identification, and DietCam is most accurate when images show food on the plate.

Research Based on Optical Non-Destructive Testing of Pigment Identification

2016 ◽  
Vol 16 (4) ◽  
pp. 3583-3586 ◽  
Author(s):  
Jigang Wang ◽  
Shengcai Hao ◽  
Wenhua Zhou ◽  
Xiaokun Qi ◽  
Jilong Shi
Keyword(s):  
Three Dimensional ◽  
Potential Method ◽  
Identification System ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
X Ray ◽  
Ultramarine Blue ◽  
Bright Yellow ◽  
Cultural Relic ◽  
Non Destructive

Optical Non-Destructive Testing (ONDT) can be applied as penetrating elemental and structure analysis technology in the pigments identification field. Three-dimensional video microscopy, Raman microscopy and energy dispersive X-ray fluorescence spectroscopy are employed to measure the materials based on a Qing Dynasty meticulous painting. The results revealed that the dark yellow area within the decorative patterns was presented due to the interaction of Emerald green and hematite, and the bright yellow edge area was delineated by Cu–Zn–Pb composition. The interesting thing is that an artificial synthetic ultramarine blue was checked in the painting. According to the first synthesized time of ultramarine blue and Paris green, the time limit of the painting completion can be identified. The principle of Pigment subtractive colorant and nitikaset method were employed to interpreting the results. Optical testing combined with the area of cultural relic identification can be a potential method to build an expert identification system successfully. This work also help lay the optical method groundwork for further cultural relic identification, sterilization, and preservation.

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