Design and development of automatic visual inspection system for PCB manufacturing

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. This paper proposes two inspection modules for an automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localisation and segmentation. The “back-end” inspection involves the classification of solder joints using the Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. The Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. This system could contribute to the development of automated non-contact, non-destructive and low cost solder joint quality inspection systems.

Automatic inspection of metallic surface defects using genetic algorithms

This paper is concerned with the problem of automatic inspection of metallic surface using machine vision. An experimental system has been developed to take images of external metallic surfaces and an intelligent approach based on morphology and genetic algorithms is proposed to detect structural defects on bumpy metallic surfaces. The approach employs genetic algorithms to automatically learn morphology processing parameters such as structuring elements and defect segmentation threshold. This paper describes the detailed procedures which include encoding scheme, genetic operation and evaluation function.

The proposed method has been implemented and tested on a number of metallic surfaces. The results suggest that the method can provide an accurate identification to the defects and can be developed into a viable commercial visual inspection system.

Comparison of visual inspection and structural-health monitoring as bridge condition assessment methods

This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems. In this study, the intended functionality of both approaches was evaluated on its ability to identify potential structural damage and to provide decision-making support. Inspection and monitoring are compared in terms of their functional performance, cost, and barriers (real and perceived) to implementation. Both methods have strengths and weaknesses across the metrics analyzed, and it is likely that a hybrid evaluation technique that adopts both approaches will optimize efficiency of condition assessment and ultimately lead to better decision making.

Comparison of visual inspection, radiographic examination, laser fluorescence and their combinations on treatment decisions for occlusal surfaces

Purpose: To compare visual inspection (VI), radiographic examination (RX) and the laser fluorescence device DIAGNOdent (L), as well as their combinations in vitro regarding treatment decisions for occlusal surfaces. Methods: 72 extracted human permanent teeth (molars and premolars) were used. Treatment decisions were recorded by three calibrated examiners, and the options available were fissure sealant and conservative restoration. For validation of treatment decisions, the teeth were sectioned and examined in a stereomicroscope. Thereafter, dental slices were scanned and the images were edited to facilitate classification of existing carious lesions. Intra and inter-examiner reproducibility for the determination of treatment plans were calculated using Cohen's kappa test (95%-CI). Sensitivity, specificity, positive and negative predictive values, and the area under the ROC curve were also calculated. Results: VI and L provided on average the greatest intra- and inter-examiner reproducibility, respectively. Although the combination of diagnostic methods may decrease both intra- and inter examiners reproducibility, combination of VI, L and RX resulted in the greatest sensitivity, being statistically superior to RX and L. There was more inter-examiner agreement for the option of restorative treatment, while the use of sealants as a treatment option yielded the lowest values. Negative predictive values were numerically inferior to positive predictive values, indicating that the examiners preferred not to restore a carious tooth than to proceed operatively in an intact tooth. The combination of the three methods studied showed the best results in determining treatment plans for occlusal surfaces, when compared to the other types of exams. on the other hand, radiographic examination and laser fluorescence were less efficient when used alone.

In situ and in vitro comparison of laser fluorescence with visual inspection in detecting occlusal caries lesions

The aim of this study was to compare the in situ and in vitro performances of a laser fluorescence (LF) device (DIAGNOdent 2095) with visual inspection for the detection of occlusal caries in permanent teeth. Sixty-four sites were selected, and visual inspection and LF assessments were carried out, in vitro, three times by two independent examiners, with a 1-week interval between evaluations. Afterwards, the occlusal surfaces were mounted on the palatal portion of removable acrylic orthodontic appliances and placed in six volunteers. Assessments were repeated and validated by histological analysis of the tooth sections under a stereomicroscope. For both examiners, the highest intra-examiner values were observed for the visual inspection when in vitro and in situ evaluations were compared. The inter-examiner reproducibility varied from 0.61 to 0.64, except for the in vitro assessment using LF, which presented a lower value (0.43). The methods showed high specificity at the D(1) threshold (considering enamel and dentin caries as disease). In vitro evaluations showed the highest values of sensitivity for both methods when compared to the in situ evaluations at D(1) and D(2) (considering only dentinal caries as the disease) thresholds. For both methods, the results of sensitivity (at D(1) and D(2)) and accuracy (at D(1)) showed significant differences between in vitro and in situ conditions. However, the sensitivity (at D(1) and D(2)), specificity and accuracy (both at D(1)) of the methods were not significantly different when the same condition was considered. It can be concluded that visual inspection and LF showed better performance in vitro than in situ.

DIAGNOSIS of REGIONAL CEREBRAL BLOOD FLOW ABNORMALITIES USING SPECT: AGREEMENT BETWEEN INDIVIDUALIZED STATISTICAL PARAMETRIC MAPS and VISUAL INSPECTION BY NUCLEAR MEDICINE PHYSICIANS WITH DIFFERENT LEVELS of EXPERTISE IN NUCLEAR NEUROLOGY

INTRODUCTION: Visual analysis is widely used to interpret regional cerebral blood flow (rCBF) SPECT images in clinical practice despite its limitations. Automated methods are employed to investigate between-group rCBF differences in research Studies but have rarely been explored in individual analyses.OBJECTIVES: To compare visual inspection by nuclear physicians with the automated statistical parametric mapping program using a SPECT dataset of patients with neurological disorders and normal control images.METHODS: Using statistical parametric mapping, 14 SPECT images from patients with various neurological disorders were compared individually with a databank of 32 normal images using a statistical threshold of p<0.05 (corrected for multiple comparisons at the level of individual voxels or clusters). Statistical parametric mapping results were compared with Visual analyses by a nuclear physician highly experienced in neurology (A) as well as a nuclear physician with a general background of experience (B) who independently classified images as normal or altered, and determined the location of changes and the severity.RESULTS: of the 32 images of the normal databank, 4 generated maps showing rCBF abnormalities (p<0.05, corrected). Among the 14 images from patients with neurological disorders, 13 showed rCBF alterations. Statistical parametric mapping and physician A completely agreed on 84.37% and 64.28% of cases from the normal databank and neurological disorders, respectively. The agreement between statistical parametric mapping and ratings of physician B were lower (71.18% and 35.71%, respectively).CONCLUSION: Statistical parametric mapping replicated the findings described by the more experienced nuclear physician. This finding suggests that automated methods for individually analyzing rCBF SPECT images may be a valuable resource to complement visual inspection in clinical practice.

Automatic visual dictionary generation through Optimum-Path Forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.

Automatic visual dictionary generation through optimum-path forest clusteringautomatic visual dictionary generation through optimum-path forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation.

In situ and in vitro comparison of laser fluorescence with visual inspection in detecting occlusal caries lesions

The aim of this study was to compare the in situ and in vitro performances of a laser fluorescence (LF) device (DIAGNOdent 2095) with visual inspection for the detection of occlusal caries in permanent teeth. Sixty-four sites were selected, and visual inspection and LF assessments were carried out, in vitro, three times by two independent examiners, with a 1-week interval between evaluations. Afterwards, the occlusal surfaces were mounted on the palatal portion of removable acrylic orthodontic appliances and placed in six volunteers. Assessments were repeated and validated by histological analysis of the tooth sections under a stereomicroscope. For both examiners, the highest intra-examiner values were observed for the visual inspection when in vitro and in situ evaluations were compared. The inter-examiner reproducibility varied from 0.61 to 0.64, except for the in vitro assessment using LF, which presented a lower value (0.43). The methods showed high specificity at the D(1) threshold (considering enamel and dentin caries as disease). In vitro evaluations showed the highest values of sensitivity for both methods when compared to the in situ evaluations at D(1) and D(2) (considering only dentinal caries as the disease) thresholds. For both methods, the results of sensitivity (at D(1) and D(2)) and accuracy (at D(1)) showed significant differences between in vitro and in situ conditions. However, the sensitivity (at D(1) and D(2)), specificity and accuracy (both at D(1)) of the methods were not significantly different when the same condition was considered. It can be concluded that visual inspection and LF showed better performance in vitro than in situ.