Real-time image processing and display in object size detection based on VC++

Real-time detection for object size has now become a hot topic in the testing field and image processing is the core algorithm. This paper focuses on the processing and display of the collected dynamic images to achieve a real-time image pro- cessing for the moving objects. Firstly, the median filtering, gain calibration, image segmentation, image binarization, cor- ner detection and edge fitting are employed to process the images of the moving objects to make the image close to the real object. Then, the processed images are simultaneously displayed on a real-time basis to make it easier to analyze, understand and identify them, and thus it reduces the computation complexity. Finally, human-computer interaction （HCI）-friendly in- terface based on VC ＋＋ is designed to accomplish the digital logic transform, image processing and real-time display of the objects. The experiment shows that the proposed algorithm and software design have better real-time performance and accu- racy which can meet the industrial needs.

Determination of gold nanoparticles in natural water using single particle-ICP-MS

A reliable method for detecting nanoparticles is necessary for the wide application of nanomaterials. Single particle-inductively coupled plasma mass spectrometry(SP-ICP-MS) was investigated to detect the size of gold nanoparticles(Au NPs) in this work. Discrimination of particle signal and iterative algorithm were used to calculate the baseline of particle signal. Influence of dwell time was discussed and 3 ms was selected as dwell time for size detection. Different Au NPs standards(30, 60, 80 and 100 nm) and mixed samples(60 and 100 nm) were determined by SP-ICP-MS and the accuracy was confirmed with reference values. The particle size detection limit was 19 nm in ultrapure water(UP water) and 31 nm in 0.1 μg/L Au^(3+) solution. Stability of Au NPs in ultrapure water and natural water samples was investigated by detecting size variation of AuN Ps. The result shows that Au NPs are stable in aqueous environment for 6 d but degraded after 30 d.

Estimation of citrus canker lesion size using hyperspectral reflectance imaging

The Citrus industry has need for effective approaches to remove fruit with canker before they are shipped to selective international market such as the European Union.This research aims to determine the detectable size limit for cankerous lesions using hyperspectral imaging approaches.Previously developed multispectral algorithms using visible to near-infrared wavelengths,were used to segregate cankerous citrus fruits from other peel conditions(normal,greasy spot,insect damage,melanose,scab and wind scar).However,this previous work did not consider lesion size.A two-band ratio method with a simple threshold based classifier(ratio of reflectance at wavelengths 834 nm and 729 nm),which gave maximum overall classification accuracy of 95.7%,was selected for lesion size estimation in this study.The smallest size of cankerous lesion detected in terms of equivalent diameter was 1.66 mm.The effect of variation of threshold values and number of erosion cycles(applying morphological erosion multiple times to the image)on estimation of smallest detectable lesion was observed.It was found that small threshold values gave better canker classification accuracies,while exhibiting a lower overall classification accuracy.Meanwhile,higher threshold values portrayed the opposite tendency.The threshold value of 1.275 gave the optimum tradeoff between canker classification accuracy,overall classification accuracy and minimal lesion size detection.Increasing the number of erosion cycles reduced detection rates of smaller canker lesions,leading to the conclusion that a single erosion cycle gave the best size estimation results.The erosion kernel of the size 3 mm×3 mm was used during the exploration.