Kernel-like impurity detection according to colour band spectral image using GA/SVM

Kernel-like impurities (KLIs) have the similar colour, shape, texture and specific gravity with sound kernels. The amount of the KLIs is an important parameter for evaluating the quality of wheat. However, it is difficult to classify KLIs from sound kernels with normal methods because of these similar features. In this study, a machine vision system with a linear colour charged coupled device used to acquire images of kernels and a software package developed to extract various features from the images were used to classify 1169 sound kernels and 896 KLIs. Three methods—genetic algorithm (GA)/support vector machine (SVM), principal components analysis/SVM and linear discriminant analysis—were applied for the classification. The performance of GA/SVM for detecting KLIs was very outstanding, and the accuracy of testing sets could reach 99.34%. GA/SVM has the potential to improve the KLI classification accuracy in machine vision system. It is feasible to extract a small quantity of useful features without any extra image or data processing for online KLI classification.     

Hybrid retinal image registration using phase correlation

Abstract

This paper deals with registration of retinal images, which were taken by high-resolution digital colour fundus cameras. The proposed method describes successful application of phase correlation method. It combines several basic steps — global correction of shift, rotation and scaling, detection of landmarks, their correspondences and finally image registration using second-order polynomial model. The method is tested on two sets of images. The first set contains images from the diabetic patients where many retinal pathologies can disturb the registration process. The second set contains images from healthy subjects, which were acquired by different illumination conditions. The method was evaluated using four different criteria - tree objective and one subjective. These criteria are also compared. The achieved registration accuracy of the landmarks position error is 1·13 and 0·93 pixels for respective image sets. Finally, the simple scheme for retinal pathology visualisation of registered fundus pairs is presented.     

Prediction of oil and oleic acid concentrations in individual corn (Zea mays L.) kernels using near-infrared reflectance hyperspectral imaging and multivariate analysis

Due to their heterogeneous structure and variability in form, individual corn (Zea mays L.) kernels present an optical challenge for nondestructive spectroscopic determination of their chemical composition. Increasing demand in agricultural science for knowledge of specific traits in kernels is driving the need to find high-throughput methods of examination. In this study macroscopic near-infrared (NIR) reflectance hyperspectral imaging was used to measure small sets of kernels in the spectroscopic range of 950 nm to 1700 nm. Image analysis and principal component analysis (PCA) were used to determine kernel germ from endosperm regions as well as to define individual kernels as objects out of sets of kernels. Partial least squares (PLS) analysis was used to predict oil or oleic acid concentrations derived from germ or full kernel spectra. The relative precision of the minimum cross-validated root mean square error (RMSECV) and root mean square error of prediction (RMSEP) for oil and oleic acid concentration were compared for two sets of two hundred kernels. An optimal statistical prediction method was determined using a limited set of wavelengths selected by a genetic algorithm. Given these parameters, oil content was predicted with an RMSEP of 0.7% and oleic acid content with an RMSEP of 14% for a given corn kernel.     

Single sand-dust image restoration using information loss constraint

Abstract

Outdoor images captured during sand–dust weather condition typically yield poor contrast and colour shift. A novel method for single sand–dust images restoration is introduced in this paper, which relies on the atmospheric scattering model and information loss constraint. To compensate the colour shift and achieve proper luminance, the proposed atmospheric light is changing with the content of the local scenes, which is initially estimated on the basis of the general scattering model and the grey-world assumption. Then, the initial atmospheric light is updated and the coarse transmission is estimated under the information loss constraint. Next, the fast guide filter is exploited in the post-refinement process to inhibit the halo artefacts. Comparison experiments demonstrate that the proposed algorithm is straightforward and efficient, the contrast and colour shift of different kinds of sand-dust images can be well compensated, especially, nice colour fidelity and proper luminance can be maintained.     

Insoluble phase in Al–1·52Cu–0·75Mg alloys containing silicon

Abstract

Insoluble particles present in solution treated, quenched and aged Al–1·52Cu–0·75Mg alloys containing 0·23, 0·49, 0·76, and 1·03 wt-% Si have been investigated. Back-scattered scanning electron microscope images of polished sections of the alloys showed the presence of very small, nearly spherical particles at the grain boundaries of all alloys except that containing 0·23 wt-% Si. Alloys with 0·76 and 1·03 wt-% Si also contained large particles of well defined geometrical shapes. An electrolytic technique was used to extract the insoluble particles from the matrix. The extracted particles were analysed by energy dispersive X-ray analysis in a scanning electron microscope. They contained 20·6±0·4%Cu, 32·6±0·4%Mg, 30·2±0·4%Si, and 16·6±0·1%Al (all wt-%). X-ray diffraction analysis of these particles showed that they have a hexagonal structure with lattice parameters a=1·036±0·004 nm and c=0·404±0·004 nm. The insoluble particles were identified as quarternary phase Q. Aging for extended periods at 190°C did not alter the composition or morphology of the insoluble particles.

MST/661     

小样本药用玻璃瓶缺陷生成方法及应用

目的 为了克服药包玻璃瓶缺陷样本不足带来的缺陷检测模型精度不准的问题,提出改进StyleGAN2-ADA的缺陷样本生成方法,提升模型鲁棒性。方法 首先,基于StyleGAN2-ADA算法,在无缺陷图像集上训练网络模型并作为骨干。其次,在骨干网络上添加缺陷感知残差块,生成缺陷掩码,在少量的缺陷图像数据集上训练网络模型操纵掩码区域的特征,模拟缺陷图像生成过程,合成缺陷图像。最后,采用YOLOv7检测网络验证该样本生成方法的效果。结果 实验结果表明,该方法在大量正常图像和少量缺陷图像基础上生成逼真且多样性的缺陷图像,应用该缺陷样本合成方法丰富数据集后,西林瓶缺陷检测平均准确率（mAP）达到97.3%,较原始数据集合和StyleGAN2-ADA算法分别提高了33.1%和4.1%。结论 该图像生成方法可以在少量缺陷样本下生成高质量的缺陷图像,优化不均衡数据集,增强模型训练的稳定性,提高药用玻璃包装产品的质量和合格率。     

Growth and characterisation of KNbO2 single crystals

Abstract

The growth of good quality colourless potassium niobate (KNbO₃) single crystals is reported. Various flux compositions with corresponding starting temperatures were chosen from the phase diagram to avoid the black/blue colour formation in growth of KNbO₃ single crystals. Deviation of compositions of colourless and black crystals from the starting composition were analysed by electron spectroscopy for chemical analysis. Dielectric constant and pyroelectric coefficients were calculated with respect to temperature and the transition temperature was confirmed by differential scanning calorimetry studies. Hysteresis loops have been traced with respect to electric field.     

Artificial neural network modelling to predict hot deformation behaviour of as HIPed FGH4169 superalloy

Abstract

The hot deformation behaviour of as HIPed FGH4169 superalloy was studied by single stroke compression test on MMS-200 test machine at the temperatures of 950–1050°C and the strain rates of 0·004–10 s^?1. Based on the experimental results, a back-propagation artificial neural network model and constitutive equation method were established to predict the flow stress of FGH4169 superalloy. The predictability of two different models was compared. The correlation coefficients of experimental and predicted flow stress with the trained BP ANN model and constitutive equation were 0·9995 and 0·9808 respectively. The average root mean square error (RMSE) values of the trained ANN model and constitutive equation are 0·39 and 2·21 MPa respectively. And the average absolute relative error (AARE) values of the trained ANN model and constitutive equation are 1·79 and 7·47% respectively. The results showed that the ANN model is an effective tool to predict the flow stress in comparison with constitutive equation.     

Optimization of discriminant partial least squares regression models for the detection of animal by-product meals in compound feedingstuffs by near-infrared spectroscopy

This paper evaluates two multivariate strategies for classifying near-infrared (NIR) spectroscopic data for the detection of animal by-product meals (henceforth generically termed AbP) as an ingredient in compound feedingstuffs. Classification models were developed to discriminate between the presence and absence of animal-origin meals in compound feeds using two forms of discriminant partial least squares (PLS) regression: the algorithms PLS1 and PLS2. The training set comprised 433 commercial feeds, of which 148 contained AbP and the other 285 were stated to be AbP-free. Since the initial set contained unequal numbers of each class, the effect of this imbalance was analyzed by applying the same algorithms to a training set containing equal numbers of AbP-free and AbP-containing samples. The best classification model (97.42% of samples correctly classified), obtained with PLS2, that showed less sensitivity to the use of class-unbalanced sets, was externally validated using a set of 18 samples (10 AbP-containing and 8 AbP-free); all samples were correctly classified, except for one AbP-free sample that was classified as containing AbP (false positive). The results suggest that the application of PLS discriminant analysis to NIR spectroscopic data enables detection of AbP, a feed ingredient banned since the bovine spongiform encephalopathy (BSE) crisis; this confirms the value of NIRS qualitative analysis for product authentication purposes.     

Fast Watersnakes: an improved image segmentation framework

Fissure detection is an important task in the interpretation and diagnosis of pathologies present in lung CT images and has a lot of challenges in terms of speed and accuracy. In this paper, a new method called Fast Watersnakes to detect and segment the fissures has been proposed. Fast Watersnakes integrates the speed of Fast Watershed and the smoothness of active contours to obtain the desirable segmentation. Fast Watershed based on chain codes provides a prominent solution to the over-segmentation problem of morphological watersheds. However, there is no control of smoothness in the segmentation results. Existing methods use watershed line and contour length to incorporate smoothness, but there are no watershed lines in Fast Watersheds. The proposed method addresses Fast Watersheds as energy minimisation function. Experimental results show that the proposed method overcomes the over-segmentation problem and shows a considerable reduction in root mean square (RMS) error values when tested with lung CT images. The proposed method gives an RMS error range of 1·98±1·60 mm for fissure segmentation when compared with expert observations.     

Sulfonated carbon black-based composite membranes for fuel cell applications

Two different commercial grade carbon black samples, Cabot Regal 400R (C1) and Cabot Mogul L (C2), were sulfonated with diazonium salt of sulfanilic acid. The resultant sulfonated carbon black samples (S–C) were characterized by Fourier transform infrared spectroscopy (FTIR) and thermal gravimetric analysis (TGA). Composite membranes were then prepared using S–C as fillers and sulfonated poly(ether ether ketone) (SPEEK) as polymer matrix with three different sulfonation degrees (DS = 60, 70 and 82%). Structure and properties of the composite membranes were characterized by FTIR, TGA, scanning electron microscopy, proton conduction, water uptake, ion exchange capacity and chemical stability. Incorporation of S–C particles above 0· 25 wt% caused decrease in chemical stability. Pristine and composite membranes prepared from SPEEK82 decomposed completely in $\boldsymbol{<}$ 1 h, which is undesirable for fuel cell applications. SPEEK60 membrane having wt% of 0·25–0· 5 with S–C particles led to higher proton conductivity than that of pristine membrane. No positive effect was observed on the properties of the composite membranes with the addition of S–C particles at high concentrations due to the agglomeration problems and decrease in the content of conductive polymer matrix.     

A colour image retrieval scheme based on Z-scanning technique

Abstract

This paper proposes a new colour image retrieval scheme using Z-scanning technique for content-based image retrieval (CBIR). In recent years, the CBIR is a popular research topic for image retrieval. This paper proposes a scheme which employs the Z-scanning technique to extract directional intensity features for measuring the similarity between query and database images. In the multiple channel images, each colour channel can be processed individually or combined into a grey channel Y. In order to extract the features by Z-scanning technique from all images, each channel of all images must be divided into several N×N blocks. In each block, F pairs of pixels are scanned by a ‘Z’ direction to obtain the texture features. Each colour channel can be obtained an M×M Z-scanning co-occurrence matrix (ZSCM) for storing the probability of each relationship of all closest blocks. At the similarity measure stage, the ZSCMs of query image and database images are compared to measure their similarity. The experimental results show that the proposed scheme is beneficial for image retrieval when the images include the same texture or object. On the other hand, the proposed scheme also can get better retrieval results and more efficiency than colour correlogram (CC) technique for colour texture images. Another technique uses motif co-occurrence matrix (MCM) as the feature in similarity measurement. The experimental results show the proposed ZSCM can get better retrieval results and higher recall and precision values than the CC and MCM techniques for public image databases.     

Effect of heterogeneous deformation on precipitate distribution in Al–3·7Cu and Al–3·8Cu–1·8Mg alloys

Abstract

Cold rolling and hot rolling of solution treated Al–3·7Cu and Al–3·8Cu–1·8Mg alloys were performed to test the effect of inhomogeneous precipitation in shear bands during following aging of the material. The most effective inhomogeneous distribution of particles was observed for samples hot deformed and aged within the temperature range 473–573 K. It was noted that magnesium addition intensifies coarse shear bands development and following coarsening of particles within sheared area.     

Influence of nodule count on fatigue properties of ferritic thin wall ductile iron

Abstract

The present work focuses on the study of the influence of nodule count on the fatigue resistance of ductile iron. Fatigue tests were carried out on specimens taken from thin wall ductile iron plates of 2 and 4 mm thickness and standard Y blocks of 12·7 mm thickness, showing nodule counts ranging between 1800 and 300 nod mm^?2. All samples were ferritised before testing to obtain a homogeneous ferritic matrix. The results showed a large dispersion of fatigue strength values. Nevertheless, careful examination of the fracture surfaces showed the presence of very small casting defects on many test samples. When only the results measured on sound test samples were accounted for, a significant increase in fatigue strength was found as the nodule count increases. Casting defects, particularly microshrinkage, revealed by scanning electron microscopy on the fracture surfaces, were responsible for the premature failure, due to shortening of the crack initiation stage. The fatigue lives measured experimentally were compared with estimations based on the fracture mechanics theory.     

Magnetostriction of duplex stainless steels

Abstract

To identify suitable non-destructive examination techniques, the saturation magnetostriction of a number of ferritic–austenitic (duplex) stainless steel samples from various manufacturers has been measured using a dilatometric technique. The values were found to lie in two distinct ranges, which suggested that two types of material structure were present, often in the same steel type. By examination of optical micrographs of all the samples, it was confirmed that the two ranges of saturation magnetostriction corresponded to two types of structure as follows: (15·5 ±3·3) ×10^?6 (average) in the rolling direction for highly anisotropic material structure and (5·7 ± 2·2) × 10^?6 (average) for isotropic material independent of orientation and for highly anisotropic material perpendicular to the rolling direction.

MST/945     

Emission spectrographic technique for the quantitative determination of trace elements in granitic rocks

An emission spectrographic technique was developed to estimate 16 trace elements in some samples of Egyptian granite. The detection limits were: 0·1 ppm for Pb, Ba, Mo, Cu, Cr, Yb and Ni, 0·3 ppm for Sn, Ga and Be, 1 ppm for Co, Sc and V, 3 ppm for Bi and Y and 10 ppm for La. The relative deviation of the two-thirds limits ranges between ± 1·5 and ±24·7.     

Preparation and characterisation of fluorescent polystyrene spheres coated with different sized quantum dots

Abstract

Water soluble CdSe quantum dots (QDs) coated polymer sphere with single and multiple fluorescent peaks have been prepared through the layer by layer self-assembly method. Polystyrene (PS) spheres ranging mainly from 330 to 750 nm and from 1·0 to 3·5 μm were used as the templates for deposition of three sized fluorescent QDs. The results of transmission electron microscopy and fluorescent confocal optical slice showed that the PS/CdSe composites were spherical in shape with core–shell structures. Emission colours of the mixture of spheres with single colour signal emitting at different wavelengths stimulated by a single light source could be distinguished clearly. Single spheres with separated, multiple fluorescence peaks could be easily obtained by controlling the ratios of the three sized CdSe QDs.     

Defect detection in CFRP structures using pulsed thermographic data enhanced by penalized least squares methods

Pulsed thermography (PT) is a widely used non-destructive testing (NDT) method for detecting defective regions in carbon fiber reinforced polymers (CFRP) structures. In order to improve the spatial and temporal resolution of thermographic data, thermographic signal reconstruction (TSR) is often adopted for data processing and analysis. However, TSR only performs data filtering along the time direction, while the spatial information is not exploited for noise reduction. In addition, TSR cannot handle the non-uniform backgrounds commonly existing in thermal images. To get around these problems, this paper extends the utilization of the penalized least squares methods to defect detection in CFRP structures. The experiment results show that, with the aid of penalized least squares, the defective regions in thermal images are characterized more clearly, while the signal-to-noise ratio (SNR) values are increased significantly.     

Pixel expansion-free grey-scale image sharing method

Abstract

In recent years, many visual secret sharing technologies have been proposed to protect the security of secret images (black and white, grey scale or colour images). In 2005, Lukac and Plataniotis used the concept of the Naor–Shamir method to propose a visual secret sharing technology for sharing secret grey-scale images based on bit-plane decomposition. Although their method can avoid pixel-value cutting problem, it still suffers from the pixel expansion problem. In this paper, we propose a new secret grey-scale image sharing method to improve this situation. In the proposed sharing image creation phase, two sharing images (one is grey-scale and the other is binary) are created and later shared by two protectors. The original secret image can be easily reconstructed if both sharing images are obtained. However, one cannot obtain the original secret image from each of the sharing images. Experimental results also show that the proposed method can effectively solve the pixel expansion problem.     

Continuous separation of Fe–Al–Zn dross phase from hot dip galvanised melt using alternating magnetic field

Abstract

Experiments to continuously separate Fe–Al–Zn dross phase from hot dip galvanising zinc melt were conducted on a laboratory scale apparatus by using high frequency alternating magnetic field. Effects of processing time (t) on separation efficiency were investigated. The experimental results show that using the electromagnetic repulsive force resulting from the electrical conductivity difference between zinc melt and Fe–Al–Zn dross phase, the deleterious zinc dross particles causing surface defects of galvanising steel sheets can be continuously separated from the zinc bath under alternating magnetic field, and the separation efficiency increases with the increase in processing time. When the magnetic frequency is 17·5 kHz, the effective magnetic flux intensity is 0·1 T, the cross-section of the ceramic square pipe is 10 × 10 mm, and the processing time is 0·6–2·5 s, the separation efficiency of zinc dross varies from 43·76 to 85·71%, and the experimental results are in reasonable agreement with the theoretical results.