The Effect of Periodic Segmentation Cracks on the Interfacial Debonding: Study on Interfacial Stresses

Hard coatings on relatively soft substrate always face the danger of debonding along the interface. Interfacial stresses are considered to be the initial driving force for the interfacial debonding of the relatively strong bonded coatings. Interfacial stresses due to the mismatch of strain between the coating and substrate are simulated with FEM firstly. The distribution of the interfacial stresses is achieved, which confirms an excessive stresses concentration near the interface end. Subsequently, the redistribution of interfacial stresses is calculated for a coating with periodic segmentation cracks. Results indicate that the distribution of interfacial stresses is altered greatly with the periodic segmentation cracks. To reveal the effect of the spacing of the periodic segmentation cracks on the distribution of interfacial stresses, different crack density is modeled within the coating. It is found that that the peak values of the interfacial stresses decrease with the increase of crack density, i.e. with reduction of spacing of segmentation cracks.

On the Formation of Periodic Segmentation Cracks in a Coating Plated on a Substrate with Periodic Subsurface Inclusions

The mechanism of the formation of periodic segmentation cracks of a coating plated on a substrate with periodic subsurface inclusions (PSI) is investigated. The internal stress in coating and subsequently the strain energy release rate (SERR) of the segmentation cracks are computed with finite element method (FEM). And the effect of the geometrical parameters of the PSI is studied. The results indicate that the ratio of the width of the inclusion to the period of the repeated structure has an optimum value, at which the maximum internal tensile stress and SERR arise. On the other hand, the ratio of the max-thickness of the inclusion to the thickness of the coating has a threshold value, above which the further increase of this ratio should seldom influence the internal stress or the SERR.

On The Interaction Of Channeling/Segmentation Cracks Of Coating: Study On The Critical Spacing

Channeling/segmentation cracks may arise in the coating subjected to in-plane tensile stress. The interaction between these multiple cracks, say the effect of the spacing between two adjacent cracks oil the behaviors of channels themselves and the interface around the interface corners, attracts wide interest. However, if the spacing is greater than a specific magniture,, namely the Critical Spacing (CS), there should be no interaction between such channeling/segmentation cracks. In this study, file mechanism of the effect of the crack spacing oil the interfacial stress around the interface corner will be Interpreted firstly. Then the existence of the CS will be verified and the relationship between the CS and the so-called stress transfer length Ill coating will be established for plane strain condition. Finally, the dependence of the stress transfer length, simultaneously of the CS, on the sensitive parameters will be investigated with finite element method and expressed with a simple empirical formula. (C) 2007 Elsevier Ltd. All rights reserved.

Novel approach for region merging and image segmentation for human-computer interaction

For the purpose of human-computer interaction (HCI), a vision-based gesture segmentation approach is proposed. The technique essentially includes skin color detection and gesture segmentation. The skin color detection employs a skin-color artificial neural network (ANN). To merge and segment the region of interest, we propose a novel mountain algorithm. The details of the approach and experiment results are provided. The experimental segmentation accuracy is 96.25%. (C) 2003 Society of Photo-Optical Instrumentation Engineers.

Spatiotemporal segmentation based on two-dimensional spatiotemporal entropic thresholding

A novel spatiotemporal segmentation technique is further developed for extracting uncovered background and moving objects from the image sequences, then the following motion estimation is performed only on the regions corresponding to moving objects. The frame difference contrast (FCON) and local variance contrast (LCON), which are related to the temporal and spatial homogeneity of the image sequence, are selected to form the 2-D spatiotemporal entropy. Then the spatial segmentation threshold is determined by maximizing the 2-D spatiotemporal entropy, and the temporal segmentation point is selected to minimize the complexity measure for image sequence coding. Since both temporal and spatial correlation of an image sequence are exploited, this proposed spatiotemporal segmentation technique can further be used to determine the positions of reference frames adaptively, hence resulting in a low bit rate. Experimental results show that this segmentation-based coding scheme is more efficient than usual fixed-size coding algorithms. (C) 1997 Society of Photo-Optical Instrumentation Engineers.

A Unified Tensor Level Set for Image Segmentation

This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt-and pepper-type noise. Second, considering the local geometrical features, e. g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

A Relay Level Set Method for Automatic Image Segmentation

This paper presents a new image segmentation method that applies an edge-based level set method in a relay fashion. The proposed method segments an image in a series of nested subregions that are automatically created by shrinking the stabilized curves in their previous subregions. The final result is obtained by combining all boundaries detected in these subregions. The proposed method has the following three advantages: 1) It can be automatically executed without human-computer interactions; 2) it applies the edge-based level set method with relay fashion to detect all boundaries; and 3) it automatically obtains a full segmentation without specifying the number of relays in advance. The comparison experiments illustrate that the proposed method performs better than the representative level set methods, and it can obtain similar or better results compared with other popular segmentation algorithms.