Vision-based classification of solder joint defects

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. The solder joint inspection problem is more challenging than many other visual inspections because of the variability in the appearance of solder joints. Although many research works and various techniques have been developed to classify defect in solder joints, these methods have complex systems of illumination for image acquisition and complicated classification algorithms. An important stage of the analysis is to select the right method for the classification. Better inspection technologies are needed to fill the gap between available inspection capabilities and industry systems. This dissertation aims to provide a solution that can overcome some of the limitations of current inspection techniques. This research proposes two inspection steps for automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localization and segmentation. The illumination normalisation approach can effectively and efficiently eliminate the effect of uneven illumination while keeping the properties of the processed image. The “back-end” inspection involves the classification of solder joints by using Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. Further testing demonstrates the advantage of Log Gabor filter over both Discrete Wavelet Transform and Discrete Cosine Transform. Classifier score fusion is analysed for improving recognition rate. Experimental results demonstrate that the proposed system improves performance and robustness in terms of classification rates. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. In fact, the choice of suitable features allows one to overcome the problem given by the use of non complex illumination systems. The new system proposed in this research can be incorporated in the development of an automated non-contact, non-destructive and low cost solder joint quality inspection system.

A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

Cystine-mediated oxidative defence in Lactobacillus reuteri BR11

Lactobacillus reuteri BR11 possesses an abundant cystine uptake (Cyu) ABC-transporter that was previously found to be involved in a novel mechanism of oxidative defence mediated by cystine. The current study aimed to elucidate this mechanism with a focus on the role of the co-transcribed cystathionine ã-lyase (Cgl). Growth studies of wild-type L. reuteri BR11 and mutants inactivated in cgl and the cystine-binding protein encoding gene cyuC showed that in contrast to the Cyu transporter, whose inactivation led to growth arrest in aerated cultures, Cgl is not crucial for oxidative defence. However, the role of Cgl in oxidative defence became apparent in the presence of severe oxidative damage and cysteine deprivation. Cysteine was found to be protective against oxidative stress, and the action of Cgl in both cysteine biosynthesis and degradation poses a seemingly futile pathway that deprives the intracellular cysteine pool. To further characterise the relationship between Cgl activity and cysteine and their roles in oxidative defence, enzymatic assays were performed on purified Cgl, and intracellular concentrations of cysteine, cystathionine and methionine were determined. Cgl was highly active towards cystine and cystathionine and less active towards cysteine in vitro, suggesting the main function of Cgl to be cysteine biosynthesis. Cysteine was found at high concentrations in the cell, but the levels were not significantly affected by inactivation of cgl or growth under aerobic conditions. It was concluded that both anabolic and catabolic activities of Cgl towards cysteine contribute to oxidative defence, the former by maintaining an intracellular reservoir of thiol analogous to glutathione, and the latter by producing H2S which is readily secreted, thus creating a reducing extracellular environment. The significance of the Cyu transporter to the physiology of L. reuteri BR11 prompted a phylogenetic study to determine its presence in bacteria. Orthologs of the Cyu transporter that are closest matches to the Cyu transporter are only limited to several species of Lactobacillus and Leuconostoc. Outside the Lactobacillales order, the closest matching orthologs belong to Proteobacteria, and there are more orthologs in Proteobacteria than non-Lactobacillales Firmicutes, suggesting that the Cyu transporter locus was present in the ancestor of the Proteobacteria and Firmicutes, and over evolutionary time has been lost or diverged in many Firmicutes. The clustering of the Cyu transporter locus with a gene encoding a Cgl family protein is even rarer. It was only found in L. reuteri, Lactobacillus vaginalis, Weissella paramesenteroides, the Lactobacillus casei group, and several Campylobacter sp. An accompanying phylogenetic study of L. reuteri BR11 using multi-locus sequence analysis showed that L. reuteri BR11 had diverged from more than 100 strains of L. reuteri isolated from various hosts and geographical locations. However, comparison with other Lactobacillus species supported the current classification of BR11 as L. reuteri. The most closely related species to L. reuteri is L. vaginalis or Lactobacillus antri, depending on the housekeeping gene used for analysis. The close evolutionary relationship of L. vaginalis to L. reuteri and the high degree of sequence identity between the cgl-cyuABC loci in both species suggest that the Cyu system is highly likely to perform similar functions in L. vaginalis. In search of other genes that function in oxidative defence, a number of mutants which were inactivated in genes that confer increased resistance to oxidative stress in other bacteria were constructed. The genes targeted were ahpC (peroxidase component of the alkyl hydroperoxide reductase system), tpx (thiol peroxidase), osmC (osmotically induced protein C), mntH (Mn2+/Fe2+ transporter), gshA (ã-glutamylcysteine synthetase) and msrA (methionine sulfoxide reductase). The ahpC and mntH mutants had slightly lower minimum inhibitory concentrations of organic peroxides, suggesting these genes might be involved in resistance to organic peroxides in L. reuteri. However, none of the mutants exhibited growth defects in aerated cultures, in stark contrast to the cyuC mutant. This may be due to compensatory functions of other genes, a hypothesis which cannot be tested until a robust protocol for constructing markerless multiple gene deletion mutants in L. reuteri is developed. These results highlight the importance of the Cyu transporter in oxidative defence and provide a foundation for extending the research of this system in other bacteria.

Obesity screening for young Japanese males and females using skin fold measurements : the classification revisited

Anthropometric assessment is a simple, safe, and cost-efficient method to examine the health status of individu-als. The Japanese obesity classification based on the sum of two skin folds (Σ2SF) was proposed nearly 40 years ago therefore its applicability to Japanese living today is unknown. The current study aimed to determine Σ2SF cut-off values that correspond to percent body fat (%BF) and BMI values using two datasets from young Japa-nese adults (233 males and 139 females). Using regression analysis, Σ2SF and height-corrected Σ2SF (HtΣ2SF) values that correspond to %BF of 20, 25, and 30% for males and 30, 35, and 40% for females were determined. In addition, cut-off values of both Σ2SF and HtΣ2SF that correspond to BMI values of 23 kg/m2, 25 kg/m2 and 30 kg/m2 were determined. In comparison with the original Σ2SF values, the proposed values are smaller by about 10 mm at maximum. The proposed values show an improvement in sensitivity from about 25% to above 90% to identify individuals with ≥20% body fat in males and ≥30% body fat in females with high specificity of about 95% in both genders. The results indicate that the original Σ2SF cut-off values to screen obese individuals cannot be applied to young Japanese adults living today and modification is required. Application of the pro-posed values may assist screening in the clinical setting.

Assigning metabolic equivalent (MET) values to the 2002 Census Occupational Classification System

Background: The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories. Methods: We describe the methods and rationale for assigning detailed MET estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5,323 (2,917 males and 2,406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day. Results: Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared to using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations. Conclusions: Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.

Overview of the INEX 2010 XML mining track : clustering and classification of XML documents

The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

Towards a classification of criterion referenced assessment models in mathematics courses : student and academic perspectives

We present the findings of a study into the implementation of explicitly criterion- referenced assessment in undergraduate courses in mathematics. We discuss students' concepts of criterion referencing and also the various interpretations that this concept has among mathematics educators. Our primary goal was to move towards a classification of criterion referencing models in quantitative courses. A secondary goal was to investigate whether explicitly presenting assessment criteria to students was useful to them and guided them in responding to assessment tasks. The data and feedback from students indicates that while students found the criteria easy to understand and useful in informing them as to how they would be graded, it did not alter the way the actually approached the assessment activity.

Public service broadcasting, creative industries and innovation infrastructure : the case of ABC's Pool

The proliferation of media services enabled by digital technologies poses a serious challenge to public service broadcasting rationales based on media scarcity. Looking to the past and future, we articulate an important role that the Australian Broadcasting Corporation (ABC) might play in the digital age. We argue that historically the ABC has acted beyond its institutional broadcasting remit to facilitate cultural development and, drawing on the example of Pool (an online community of creative practitioners established and maintained by the ABC), point to a key role it might play in fostering network innovation in what are now conceptualised as the creative industries.

UAS Classification: Key to effective airworthiness and operational regulations

This presentation discusses some of the general issues relating to the classification of UAS for the purposes of defining and promulgating safety regulations. One possible approach for the definition of a classification scheme for UAS Type Certification Categories reviewed.