MRF-based texture segmentation using wavelet decomposed images

In recent textured image segmentation, Bayesian approaches capitalizing on computational efficiency of multiresolution representations have received much attention. Most of the previous researches have been based on multiresolution stochastic models which use the Gaussian pyramid image decomposition. In this paper, motivated by nonredundant directional selectivity and highly discriminative nature of the wavelet representation, we present an unsupervised textured image segmentation algorithm based on a multiscale stochastic modeling over the wavelet decomposition of image. The model, using doubly stochastic Markov random fields, captures intrascale statistical dependencies over the wavelet decomposed image and intrascale and interscale dependencies over the corresponding multiresolution region image.     

Harnessing adaptive capacity to close the pandora’s box of open innovation

ABSTRACT

This paper focuses on how companies deploy structural properties of adaptive capacity (multiplexity, redundancy and loose coupling) to cope with the phenomenon of internal challenges of Open Innovation (OI) implementation, i.e. organisational and cultural changes. We developed a single case study, which offered significant findings. First, the multiplexity of relationships in OI settings helps to face the challenges of organisational and cultural changes by triggering trust formation and interaction. Second, redundancy has twofold elements: institutional logics redundancy triggers cultural change challenges which can be overcome through management practices and communications; task redundancy facilitates knowledge sharing and collaboration, thus helping to deal with organisational change challenges. Finally, loose coupling in OI settings facilitates social interconnectedness among members through management practices, helping to face organisational and cultural change challenges. We provide managerial and theoretical implication to deal with the challenges of OI in relation to both organisational and cultural changes.     

Automatic optic disk boundary extraction by the use of curvelet transform and deformable variational level set model

Efficient optic disk (OD) localization and segmentation are important tasks in automated retinal screening. In this paper, we take digital curvelet transform (DCUT) of the enhanced retinal image and modify its coefficients based on the sparsity of curvelet coefficients to get probable location of OD. If there are not yellowish objects in retinal images or their size are negligible, we can then directly detect OD location by performing Canny edge detector to reconstructed image with modified coefficients. Otherwise, if the size of these objects is eminent, we can see circular regions in edge map as candidate regions for OD. In this case, we use some morphological operations to fill these circular regions and erode them to get final locations for candidate regions and remove undesired pixels in edge map. Since usually OD is surrounded by vessels, we choose the candidate region that has maximum summation of pixels in strongest edge map, which obtained by performing an appropriate threshold on the curvelet-based enhanced image, as final location of OD. Finally, the boundary of the OD is extracted by using level set deformable model. This method has been tested on different retinal image datasets and quantitative results are presented.     

A new analytical method for determination of discharge duration in tunnels subjected to groundwater inrush

Bulletin of Engineering Geology and the Environment - Unexpected water inrush to tunnels is one of the most hazardous events, especially in karst terrains that could take place during mechanized...     

Compressive image acquisition in modern CMOS IC design

Compressive sampling (CS) offers bandwidth, power, and memory size reduction compared to conventional (Nyquist) sampling. These are very attractive features for the design of modern complementary metal‐oxide semiconductor (CMOS) image sensors, cameras, and camera systems. However, very few integrated circuit (IC) designs based on CS exist because of the missing link between the well‐established CS theory on one side, and the practical aspects/effects related to physical IC design on the other side. This paper focuses on the application of compressed image acquisition in CMOS image sensor integrated circuit design. A new CS scheme is proposed, which is suited for hardware implementation in CMOS IC design. All the main physical non‐idealities are explained and carefully modeled. Their influences on the acquired image quality are analyzed in the general case and quantified for the case of the proposed CS scheme. The presented methodology can also be used for different CS schemes and as a general guideline in future CS based CMOS image sensor designs. Copyright © 2013 John Wiley & Sons, Ltd.     

Effects of drying methods on qualitative and quantitative properties of essential oil of two basil landraces

Sweet basil, a plant that is extensively cultivated in some countries, is used to enhance the flavour of salads, sauces, pasta and confectioneries as both a fresh and dried herb. To determine the effect of drying methods on qualitative and quantitative characteristics of the plant and essential oil of basil, two landraces, Purple and Green, were dried in sunlight, shade, mechanical ovens at 40 °C and 60 °C, a microwave oven at 500 W and by freeze-drying. For comparison, the essential oils of all samples were extracted by hydrodistillation and analyzed using GC and GC–MS. The highest essential oil yields (v/w on dry weight basis) were obtained from shade-dried tissue in both landraces followed by the freeze-dried sample of the purple landrace and the fresh sample of green landrace. Increasing the drying temperature significantly decreased the essential oil content of all samples. Significant changes in the chemical profile of the essential oils from each of the landrace were associated with the drying method, including the loss of most monoterpene hydrocarbons, as compared with fresh samples. No significant differences occurred among several constituents in the extracted essential oils, including methyl chavicol (estragole), the major compound in the oil of both landraces, whether the plants were dried in the shade or sun, oven at 40 °C or freeze-dried, as compared with a fresh sample. The percentage methyl chavicol in the oil, however, decreased significantly when the plant material was dried in the oven at 60 °C or microwaved. In addition, linalool, the second major compound in the purple landrace, and geranial and neral, major compounds in the green landrace, decreased significantly when the plant tissue was dried in the oven at 60 °C or microwaved.