The morphology of wear particle is a fundamental indicator where wear oriented machine health can be assessed. Previous research proved that thorough measurement of the particle shape allows more reliable explanation of the occurred wear mechanism. However, most of current particle measurement techniques are focused on extraction of the two-dimensional (2-D) morphology, while other critical particle features including volume and thickness are not available. As a result, a three-dimensional (3-D) shape measurement method is developed to enable a more comprehensive particle feature description. The developed method is implemented in three steps: (1) particle profiles in multiple views are captured via a camera mounted above a micro fluid channel; (2) a preliminary reconstruction is accomplished by the shape-from-silhouette approach with the collected particle contours; (3) an iterative re-projection process follows to obtain the final 3-D measurement by minimizing the difference between the original and the re-projected contours. Results from real data are presented, demonstrating the feasibility of the proposed method.
Restoring images captured under low-illuminations is an essential front-end process for most image based applications. The Center-Surround Retinex algorithm has been a popular approach employed to improve image brightness. However, this algorithm in its basic form, is known to produce color degradations. In order to mitigate this problem, here the Single-Scale Retinex algorithm is modiﬁed as an edge extractor while illumination is recovered through a non-linear intensity mapping stage. The derived edges are then integrated with the mapped image to produce the enhanced output. Furthermore, in reducing color distortion, the process is conducted in the magnitude sorted domain instead of the conventional Red-Green-Blue (RGB) color channels. Experimental results had shown that improvements with regard to mean brightness, colorfulness, saturation, and information content can be obtained.
A good edge plot should use continuous thin lines to describe the complete contour of the captured object. However, the detection of weak edges is a challenging task because of the associated low pixel intensities. Ant Colony Optimization (ACO) has been employed by many researchers to address this problem. The algorithm is a meta-heuristic method developed by mimicking the natural behaviour of ants. It uses iterative searches to find the optimal solution that cannot be found via traditional optimization approaches. In this work, ACO is employed to track and repair broken edges obtained via conventional Sobel edge detector to produced a result with more connected edges.
Images are valuable information sources for many scientific and engineering applications. However, images captured in poor illumination conditions would have a large portion of dark regions that could heavily degrade the image quality. In order to improve the quality of such images, a restoration algorithm is developed here that transforms the low input brightness to a higher value using a modified Multi-Scale Retinex approach. The algorithm is further improved by a entropy based weighting with the input and the processed results to refine the necessary amplification at regions of low brightness. Moreover, fine details in the image are preserved by applying the Retinex principles to extract and then re-insert object edges to obtain an enhanced image. Results from experiments using low and normal illumination images have shown satisfactory performances with regard to the improvement in information contents and the mitigation of viewing artifacts.
Image enhancement is an imperative step for many vision based applications. For image contrast enhancement, popular methods adopt the principle of spreading the captured intensities throughout the allowed dynamic range according to predeﬁned distributions. However, these algorithms take little or no consideration into account of maintaining the mean brightness of the original scene, which is of paramount importance to carry the true scene illumination characteristics to the viewer. Though there have been signiﬁcant amount of reviews on contrast enhancement methods published, updated review on overall brightness preserving image enhancement methods is still scarce. In this paper, a detailed survey is performed on those particular methods that speciﬁcally aims to maintain the overall scene illumination characteristics while enhancing the digital image.