Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

Road network extraction with new vectorization and pruning from high-resolution RS images

With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.

Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Accurate urban road model reconstruction from high resolution remotely sensed imagery based on Support Vector Machine and Gabor filters

In this paper, we presented an automatic system for precise urban road model reconstruction based on aerial images with high spatial resolution. The proposed approach consists of two steps: i) road surface detection and ii) road pavement marking extraction. In the first step, support vector machine (SVM) was utilized to classify the images into two categories: road and non-road. In the second step, road lane markings are further extracted on the generated road surface based on 2D Gabor filters. The experiments using several pan-sharpened aerial images of Brisbane, Queensland have validated the proposed method.

Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

Very high resolution optical satellites for DEM generation : a review

The advent of very high resolution (VHR) optical satellites capable of producing stereo images led to a new era in extracting digital elevation model which commenced with the launch of IKONOS. The special specifications of VHR optical satellites besides, the significant economic profit stimulated other countries and companies to have their constellations such as EROS-A1 and EROS-B1 as the cooperation between Israel and ImageSat. QuickBird, WorldView-1 and WorldVew-2 were launched by DigitalGlobe. ALOS and GeoEye-1 were offered by Japan and GeoEye Respectively. In addition to aforementioned satellites, Indian and South Korea initiated their own constellation by launching CartoSat-1 and KOPOSAT-2 respectively.The availability of all so-called satellites make a huge market of stereo images for extracting of digital elevation model and other correspondent applications such as, producing orthorectifcatin images and updating maps. Therefore, there is a need for a comprehensive comparison for scientific and commercial clients to choose appropriate satellite images and methods of generating digital elevation model to obtain optimum results. This paper will thus give a review about the specifications of VHR optical satellites. Then it will discuss the automatic elaborating of digital elevation model. Finally an overview of studies and corresponding results is reported.

Characterisation of carotid atheroma in symptomatic and asymptomatic patients using high resolution MRI

Background and purpose: To prospectively evaluate differences in carotid plaque characteristics in symptomatic and asymptomatic patients using high resolution MRI. Methods: 20 symptomatic and 20 asymptomatic patients, with at least 50% carotid stenosis as determined by Doppler ultrasound, underwent preoperative in vivo multispectral MRI of the carotid arteries. Studies were analysed both qualitatively and quantitatively in a randomised manner by two experienced readers in consensus, blinded to clinical status, and plaques were classified according to the modified American Heart Association (AHA) criteria. Results: After exclusion of poor quality images, 109 MRI sections in 18 symptomatic and 19 asymptomatic patients were available for analysis. There were no significant differences in mean luminal stenosis severity (72.9% vs 67.6%; p = 0.09) or plaque burden (median plaque areas 50 mm2 vs 50 mm 2; p = 0.858) between the symptomatic and asymptomatic groups. However, symptomatic lesions had a higher incidence of ruptured fibrous caps (36.5% vs 8.7%; p = 0.004), haemorrhage or thrombus (46.5% vs 14.0%; p<0.001), large necrotic lipid cores (63.8% vs 28.0%; p = 0.002) and complicated type VI AHA lesions (61.5% vs 28.1%; p = 0.001) compared with asymptomatic lesions. The MRI findings of plaque haemorrhage or thrombus had an odds ratio of 5.25 (95% CI 2.08 to 13.24) while thin or ruptured fibrous cap (as opposed to a thick fibrous cap) had an odds ratio of 7.94 (95% CI 2.93 to 21.51) for prediction of symptomatic clinical status. Conclusions: There are significant differences in plaque characteristics between symptomatic and asymptomatic carotid atheroma and these can be detected in vivo by high resolution MRI.

Assessment of inflammatory burden contralateral to the symptomatic carotid stenosis using high-resolution ultrasmall, superparamagnetic iron oxide-enhanced MRI

BACKGROUND AND PURPOSE It is well known that the vulnerable atheromatous plaque has a thin, fibrous cap and large lipid core with associated inflammation. This inflammation can be detected on MRI with use of a contrast medium, Sinerem, an ultrasmall superparamagnetic iron oxide (USPIO). Although the incidence of macrophage activity in asymptomatic disease appears low, we aimed to explore the incidence of MRI-defined inflammation in asymptomatic plaques in patients with known contralateral symptomatic disease. METHODS Twenty symptomatic patients underwent multisequence MRI before and 36 hours after USPIO infusion. Images were manually segmented into quadrants, and the signal change in each quadrant was calculated after USPIO administration. A mixed mathematical model was developed to compare the mean signal change across all quadrants in the 2 groups. Patients had a mean symptomatic stenosis of 77% compared with 46% on their asymptomatic side, as measured by conventional angiography. RESULTS There were 11 (55%) men, and the median age was 72 years (range, 53 to 84 years). All patients had risk factors consistent with severe atherosclerotic disease. All symptomatic carotid stenoses had inflammation, as evaluated by USPIO-enhanced imaging. On the contralateral sides, inflammatory activity was found in 19 (95%) patients. Contralaterally, there were 163 quadrants (57%) with a signal loss after USPIO when compared with 217 quadrants (71%) on the symptomatic side (P=0.007). CONCLUSIONS - This study adds weight to the argument that atherosclerosis is a truly systemic disease. It suggests that investigation of the contralateral side in patients with symptomatic carotid stenosis can demonstrate inflammation in 95% of plaques, despite a mean stenosis of only 46%. Thus, inflammatory activity may be a significant risk factor in asymptomatic disease in patients who have known contralateral symptomatic disease. Patients with symptomatic carotid disease should have their contralateral carotid artery followed up.

The'cave' mineral oxammite: a high resolution thermogravimetry and Raman spectroscopic study

The thermal decomposition of natural ammonium oxalate known as oxammite has been studied using a combination of high resolution thermogravimetry coupled to an evolved gas mass spectrometer and Raman spectroscopy coupled to a thermal stage. Three mass loss steps were found at 57, 175 and 188°C attributed to dehydration, ammonia evolution and carbon dioxide evolution respectively. Raman spectroscopy shows two bands at 3235 and 3030 cm-1 attributed to the OH stretching vibrations and three bands at 2995, 2900 and 2879 cm-1, attributed to the NH vibrational modes. The thermal degradation of oxammite may be followed by the loss of intensity of these bands. No intensity remains in the OH stretching bands at 100°C and the NH stretching bands show no intensity at 200°C. Multiple CO symmetric stretching bands are observed at 1473, 1454, 1447 and 1431cm-1, suggesting that the mineral oxammite is composed of a mixture of chemicals including ammonium oxalate dihydrate, ammonium oxalate monohydrate and anhydrous ammonium oxalate.

Campylobacter jejuni and campylobacter coli genotyping by high-resolution melting analysis of a flaA fragment

The highly variable flagellin-encoding flaA gene has long been used for genotyping Campylobacter jejuni and Campylobacter coli. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The objective of this study was to apply HRM analysis to flaA-based genotyping. The initial aim was to identify a suitable flaA fragment. It was found that the PCR primers commonly used to amplify the flaA short variable repeat (SVR) yielded a mixed PCR product unsuitable for HRM analysis. However, a PCR primer set composed of the upstream primer used to amplify the fragment used for flaA restriction fragment length polymorphism (RFLP) analysis and the downstream primer used for flaA SVR amplification generated a very pure PCR product, and this primer set was used for the remainder of the study. Eighty-seven C. jejuni and 15 C. coli isolates were analyzed by flaA HRM and also partial flaA sequencing. There were 47 flaA sequence variants, and all were resolved by HRM analysis. The isolates used had previously also been genotyped using single-nucleotide polymorphisms (SNPs), binary markers, CRISPR HRM, and flaA RFLP. flaAHRManalysis provided resolving power multiplicative to the SNPs, binary markers, and CRISPR HRM and largely concordant with the flaA RFLP. It was concluded that HRM analysis is a promising approach to genotyping based on highly variable genes.