An improved brain MR image binarization method as a preprocessing for abnormality detection and features extraction

This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.

Novel Adaptive Binarization Method for Degraded Document Images

Achieving a good recognition rate for degraded document images is difficult as degraded document images suffer from low contrast,bleedthrough,and nonuniform illumination effects.Unlike the existing baseline thresholding techniques that use fixed thresholds and windows,the proposed method introduces a concept for obtaining dynamic windows according to the image content to achieve better binarization.To enhance a low-contrast image,we proposed a new mean histogram stretching method for suppressing noisy pixels in the background and,simultaneously,increasing pixel contrast at edges or near edges,which results in an enhanced image.For the enhanced image,we propose a new method for deriving adaptive local thresholds for dynamic windows.The dynamic window is derived by exploiting the advantage of Otsu thresholding.To assess the performance of the proposed method,we have used standard databases,namely,document image binarization contest(DIBCO),for experimentation.The comparative study on well-known existing methods indicates that the proposed method outperforms the existing methods in terms of quality and recognition rate.

Image Preprocessing Methods Used in Meteorological Measurement of the Temperature Testing System

The meteorological measurement automatic temperature testing system has a defective image. To solve the problem such as noise and insufficient contrast, and put forward the research program for image pretreatment, the median filter, histogram equalization and image binarization, methods were used to remove noise and enhance images. Results showed that feature points were clear and accurate after the experiment. This simulation experiment prepared for the follow-up subsequent recognition process.

Crack identification method of highway tunnel based on image processing

In this paper,the images of tunnel surface are obtained by tunnel lining rapid inspection system,and tunnel crack forest dataset(TCFD)is established.The disaster characteristics of tunnel cracks are analyzed and summarized.Solutions of tunnel crack segmentation(TCS)method are developed for the detection and recognition of cracks on tunnel lining.According to the image features of the tunnel lining and the optical principal of detection equipment,effective image pre-processing steps are carried out before crack extraction.The tunnel image of TCFD is divided into appropriate number of blocks to magnify the local features of tunnel cracks.Local threshold segmentation method is used to traverse the blocks successively,and the first target block with crack is obtained.The seed in the target block were obtained by adaptive localization method and mapped to the whole image.Region growing is performed through crack seed until complete tunnel crack is extracted.The results show that the precision,recall rate and F-measure of tunnel cracks under the TCS method can reach 92.58%,93.07%and 92.82%without strong interference.According to the binary images processed by TCS method,the projection images of different types of tunnel cracks and their respective laws are obtained.Furthermore,the TCS method is implemented and deployed as a GUI software application.

Estimation of the Foliar Area by Non-Destructive Methods in Two Stages of Growth of Pepper Plants(Capsicum annuum L.)Hybrid Salvador

The present work was aimed to obtain a model for the determination of the leaf area in function of the length and width of the leaves in pepper (Capsicum annuum L.) hybrid Salvador. The research was carried out in nursery conditions at the Experimental Campus La Teodomira, located in the parish of Lodana, Santa Ana, province of Manabí, Ecuador, in 2016, in the stages of initiation of flowering and flowering-fructification. In each phase 100 physiologically mature leaves of different sizes were collected. Leaves were digitalized in a rectangle with known dimensions, which allowed the area to be calculated through the percentage of pixels of different colors. From the determination of the length and maximum width of each leaf and the estimated area through the digitization process, the regression models were obtained, selecting the better fit generated between the leaf area and the product of the length by the maximum width of the leaf (). In the initiation of flowering stage the quadratic model generated the best coefficient of determination (R2 = 0.958), whereas in the flowering-fructification stage the best coefficient of determination was achieved by the cubic model (R2 = 0.955). The practical applicability of other simpler models among the tested ones, which show a high accuracy and sacrifice a low percentage of error, is discussed.

Choroidal vascularity index in thyroidassociated ophthalmopathy:a crosssectional study

Background:Hemodynamic changes have been observed in patients with Graves'disease.The aim of our study was to evaluate choroidal vascular change using the choroidal vascularity index(CVi)in patients with thyroid-associated ophthalmopathy(TAO).Methods:In this cross-sectional observational study,40 patients affected by TAO were recruited.Forty healthy individuals,matched for age and sex,served as controls.Foveal enhanced-depth imaging optical coherence tomography scans were obtained from all participants.Images were binarized using the ImageJ software and luminal area(LA)and total choroidal area(TCA)were measured.CVI was calculated as the proportion of LA to TCA.The relation between CVI or subfoveal choroidal thickness(SFCT)and clinical activity score,exophthalmometric value,diplopia status,gender,and age was evaluated.Results:CVI was significantly higher in patients with TAO(P=0.004).No significant difference was observed in SFCT(P=0.200)and TCA(P=0.153)comparing TAO patients and healthy controls.LA was significantly higher in TAO group(P=0.045).On multiple regression analysis,CVI was associated with TCA(P=0.043).No association Was found between SFCT or CVI and TCA,clinical activity score,exophthalmometric value,Inami value,diplopia status,genderorage(P>0.05).Conclusions:This is the first study that has demonstrated an increase in CVI in eyes with TAO compared with healthy controls and has assessed its association with clinical features.

An automated pulmonary parenchyma segmentation method based on an improved region growing algorithm in PET-CT imaging

To address the incomplete problem in pulmonary parenchyma segmentation based on the traditional methods, a novel automated segmentation method based on an eight- neighbor region growing algorithm with left-right scanning and four-corner rotating and scanning is proposed in this pa- per. The proposed method consists of four main stages： image binarization, rough segmentation of lung, image denoising and lung contour refining. First, the binarization of images is done and the regions of interest are extracted. After that, the rough segmentation of lung is performed through a general region growing method. Then the improved eight-neighbor region growing is used to remove noise for the upper, mid- dle, and bottom region of lung. Finally, corrosion and ex- pansion operations are utilized to smooth the lung boundary. The proposed method was validated on chest positron emis- sion tomography-computed tomography （PET-CT） data of 30 cases from a hospital in Shanxi, China. Experimental results show that our method can achieve an average volume overlap ratio of 96.21 ± 0.39% with the manual segmentation results. Compared with the existing methods, the proposed algorithm segments the lung in PET-CT images more efficiently and ac- curately.

Choroidal vascularity index in thyroidassociated ophthalmopathy:a crosssectional study

Background:Hemodynamic changes have been observed in patients with Graves’disease.The aim of our study was to evaluate choroidal vascular change using the choroidal vascularity index(CVI)in patients with thyroidassociated ophthalmopathy(TAO).Methods:In this cross-sectional observational study,40 patients affected by TAO were recruited.Forty healthy individuals,matched for age and sex,served as controls.Foveal enhanced-depth imaging optical coherence tomography scans were obtained from all participants.Images were binarized using the ImageJ software and luminal area(LA)and total choroidal area(TCA)were measured.CVI was calculated as the proportion of LA to TCA.The relation between CVI or subfoveal choroidal thickness(SFCT)and clinical activity score,exophthalmometric value,diplopia status,gender,and age was evaluated.Results:CVI was significantly higher in patients with TAO(P=0.004).No significant difference was observed in SFCT(P=0.200)and TCA(P=0.153)comparing TAO patients and healthy controls.LA was significantly higher in TAO group(P=0.045).On multiple regression analysis,CVI was associated with TCA(P=0.043).No association was found between SFCT or CVI and TCA,clinical activity score,exophthalmometric value,Inami value,diplopia status,gender or age(P>0.05).Conclusions:This is the first study that has demonstrated an increase in CVI in eyes with TAO compared with healthy controls and has assessed its association with clinical features.