Effect of Direct Statistical Contrast Enhancement Technique on Document Image Binarization

Background:Contrast enhancement plays an important role in the image processing field.Contrast correction has performed an adjustment on the darkness or brightness of the input image and increases the quality of the image.Objective:This paper proposed a novel method based on statistical data from the local mean and local standard deviation.Method:The proposed method modifies the mean and standard deviation of a neighbourhood at each pixel and divides it into three categories:background,foreground,and problematic(contrast&luminosity)region.Experimental results from both visual and objective aspects show that the proposed method can normalize the contrast variation problem effectively compared to Histogram Equalization(HE),Difference of Gaussian(DoG),and Butterworth Homomorphic Filtering(BHF).Seven(7)types of binarization methods were tested on the corrected image and produced a positive and impressive result.Result:Finally,a comparison in terms of Signal Noise Ratio(SNR),Misclassification Error(ME),F-measure,Peak Signal Noise Ratio(PSNR),Misclassification Penalty Metric(MPM),and Accuracy was calculated.Each binarization method shows an incremented result after applying it onto the corrected image compared to the original image.The SNR result of our proposed image is 9.350 higher than the three(3)other methods.The average increment after five(5)types of evaluation are:(Otsu=41.64%,Local Adaptive=7.05%,Niblack=30.28%,Bernsen=25%,Bradley=3.54%,Nick=1.59%,Gradient-Based=14.6%).Conclusion:The results presented in this paper effectively solve the contrast problem and finally produce better quality images.

3D Reconstruction of Fruit Shape based on Vision and Edge Sections

The fruit industry has been known as one of the largest businesses in Malaysia,where most of the fruits pass through the peeling process well in advance before the final product as juice in a bottle or slices in a can.The current industrial fruit peeling techniques are passive and inefficient by cutting parts of the pulp of the fruit with peels leading to losses.To avoid this issue,a multi-axis CNC fruit peeler can be used to precisely peel the outer layer with the guidance of a 3D virtual model of fruit.In this work,a new cost-effective method of 3D image reconstruction was developed to convert 36 fruit images captured by a normal RGB camera to a 3D model by capturing a single image every 10 degrees of fruit rotation along a fixed axis.The point cloud data extracted with edge detection were passed to Blender 3D software for meshing in different approaches.The vertical link frame meshing method developed in this research proved a qualitative similarity between the output result and the scanned fruit in a processing time of less than 50 seconds.

Zero-Index Metamaterial Superstrates UWB Antenna for Microwave Imaging Detection

Metamaterials(MTM)can enhance the properties of microwaves and also exceed some limitations of devices used in technical practice.Note that the antenna is the element for realizing a microwave imaging(MWI)system since it is where signal transmission and absorption occur.Ultra-Wideband(UWB)antenna superstrates with MTM elements to ensure the signal transmitted from the antenna reaches the tumor and is absorbed by the same antenna.The lack of conventional head imaging techniques,for instance,Magnetic Resonance Imaging(MRI)and Computerized Tomography(CT)-scan,has been demonstrated in the paper focusing on the point of failure of these techniques for prompt diagnosis and portable systems.Furthermore,the importance ofMWIhas been addressed elaborately to portray its effectiveness and aptness for a primary tumor diagnosis.Other than that,MTM element designs have been discussed thoroughly based on their performances towards the contributions to the better image resolution of MWI with detailed reasonings.This paper proposes the novel design of a Zeroindex Split RingResonator(SRR)MTMelement superstrate with a UWB antenna implemented in MWI systems for detecting tumor.The novel design of the MTM enables the realization of a high gain of a superstrate UWB antenna with the highest gain of 5.70 dB.Besides that,the MTM imitates the conduct of the zeroreflection phase on the resonance frequency,which does not exist.An antenna with an MTM unit is of a 7×4 and 10×5 Zero-index SRR MTM element that acts as a superstrate plane to the antenna.Apart from that,Rogers(RT5880)substrate material is employed to fabricate the designed MTM unit cell,with the following characteristics:0.51mm thickness,the loss tangent of 0.02,as well as the relative permittivity of 2.2,with Computer Simulation Technology(CST)performing the simulation and design.Both MTM unit cells of 7×4 and 10×5 attained 0°with respect to the reflection phase at the 2.70 GHz frequency band.The first design,MTM Antenna Design 1,consists of a 7×4 MTM unit cell that observed a rise of 5.70 dB with a return loss(S11)−20.007 dB at 2.70 GHz frequency.The second design,MTM Antenna Design 2,consists of 10×5 MTM unit cells that recorded a gain of 5.66 dB,having the return loss(S11)−19.734 dB at 2.70 GHz frequency.Comparing these two MTM elements superstrates with the antenna,one can notice that the 7×4 MTM element shape has a low number of the unit cell with high gain and is a better choice than the 10×5 MTM element in realizing MTM element superstrates antenna for MWI.

Cervical cancer situation in Malaysia:A systematic literature review

Cervix cancer is one of Malaysia’s most significant cancers for women(around 12.9%,with an age-standardised incidence rate of 19.7 per 100,000).It was higher than other Asian,West,and even worldwide nations.The National Strategic Plan for Cancer Control Program 2016–2020(Health Ministry)was presented to minimize cancer and mortality.The high incidence of cervical cancer in Malaysia is mainly due to women’s insufficient knowledge about its prevention and importance.Compared with traditional literature reviews,the systemic analysis provides many advantages.A clearer review process,a more prominent field of study,and essential priorities that can manage research bias can all help to enhance these reviews.However,better integration,cooperation,and coordination between government and private sector as well as NGOs and professional organisations are essential for optimal cancer control and treatment across the country.

A Hybrid Modified Sine Cosine Algorithm Using Inverse Filtering and Clipping Methods for Low Autocorrelation Binary Sequences

The essential purpose of radar is to detect a target of interest and provide information concerning the target’s location,motion,size,and other parameters.The knowledge about the pulse trains’properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance.A low autocorrelation binary sequence(LABS)is a complex combinatorial problem.The main problems of LABS are low Merit Factor(MF)and shorter length sequences.Besides,the maximum possible MF equals 12.3248 as infinity length is unable to be achieved.Therefore,this study implemented two techniques to propose a new metaheuristic algorithm based on Hybrid Modified Sine Cosine Algorithm with Cuckoo Search Algorithm(HMSCACSA)using Inverse Filtering(IF)and clipping method to achieve better results.The proposed algorithms,LABS-IF and HMSCACSA-IF,achieved better results with two large MFs equal to 12.12 and 12.6678 for lengths 231 and 237,respectively,where the optimal solutions belong to the skew-symmetric sequences.The MF outperformed up to 24.335%and 2.708%against the state-of-the-art LABS heuristic algorithm,xLastovka,and Golay,respectively.These results indicated that the proposed algorithm’s simulation had quality solutions in terms of fast convergence curve with better optimal means,and standard deviation.

Cervical Cancer Classification Using Combined Machine Learning and Deep Learning Approach

Cervical cancer is screened by pap smear methodology for detection and classification purposes.Pap smear images of the cervical region are employed to detect and classify the abnormality of cervical tissues.In this paper,we proposed the first system that it ables to classify the pap smear images into a seven classes problem.Pap smear images are exploited to design a computer-aided diagnoses system to classify the abnormality in cervical images cells.Automated features that have been extracted using ResNet101 are employed to discriminate seven classes of images in Support Vector Machine(SVM)classifier.The success of this proposed system in distinguishing between the levels of normal cases with 100%accuracy and 100%sensitivity.On top of that,it can distinguish between normal and abnormal cases with an accuracy of 100%.The high level of abnormality is then studied and classified with a high accuracy.On the other hand,the low level of abnormality is studied separately and classified into two classes,mild and moderate dysplasia,with∼92%accuracy.The proposed system is a built-in cascading manner with five models of polynomial(SVM)classifier.The overall accuracy in training for all cases is 100%,while the overall test for all seven classes is around 92%in the test phase and overall accuracy reaches 97.3%.The proposed system facilitates the process of detection and classification of cervical cells in pap smear images and leads to early diagnosis of cervical cancer,which may lead to an increase in the survival rate in women.

Contrast Correction Using Hybrid Statistical Enhancement on Weld Defect Images

Luminosity and contrast variation problems are among the most challenging tasks in the image processing field,significantly improving image quality.Enhancement is implemented by adjusting the dark or bright intensity to improve the quality of the images and increase the segmentation performance.Recently,numerous methods had been proposed to normalise the luminosity and contrast variation.A new approach based on a direct technique using statistical data known as Hybrid Statistical Enhancement(HSE)is presented in this study.TheHSE method uses themean and standard deviation of a local and global neighbourhood and classified the pixel into three groups;the foreground,border,and problematic region(contrast&luminosity).The datasets,namely weld defect images,were utilised to demonstrate the effectiveness of the HSE method.The results from the visual and objective aspects showed that the HSE method could normalise the luminosity and enhance the contrast variation problem effectively.The proposed method was compared to the two(2)populor enhancement methods which is Homomorphic Filter(HF)and Difference of Gaussian(DoG).To prove the HSE effectiveness,a few image quality assessments were presented,and the results were discussed.The HSE method achieved a better result compared to the other methods,which are Signal Noise Ratio(8.920),Standard Deviation(18.588)and Absolute Mean Brightness Error(9.356).In conclusion,implementing the HSE method has produced an effective and efficient result for background correction and quality images improvement.