Optimization algorithms in FMRF model-based segmentation for LIDAR data and co-registered bands

In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into free, grass, building, and road regions by fusing remotely, sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model, i.e. Lagrange multiplier (LM), iterated conditional mode (ICM), and simulated annealing (SA), are compared with respect to the computational cost and segmentation accuracy. The results have shown that the FMRF model-based ICM algorithm balances the computational cost and segmentation accuracy in land-cover segmentation from LIDAR data and co-registered bands.

Fusion of motion segmentation algorithms

Many algorithms have been developed to achieve motion segmentation for video surveillance. The algorithms produce varying performances under the infinite amount of changing conditions. It has been recognised that individually these algorithms have useful properties. Fusing the statistical result of these algorithms is investigated, with robust motion segmentation in mind.

Characterisation of an amphioxus Fringe gene and the evolution of the vertebrate segmentation clock

In mouse and chick embryos, cyclic expression of lunatic fringe has an important role in the regulation of mesoderm segmentation. We have isolated a Fringe gene from the protochordate amphioxus. Amphioxus is the closest living relative of the vertebrates, and has mesoderm that is definitively segmented in a manner that is similar to, and probably homologous with, that of vertebrates. AmphiFringe is placed basal to vertebrate Fringe genes in molecular phylogenetic analyses, indicating that the duplications that formed radical-, manic- and lunatic fringe are specific to the vertebrate lineage. AmphiFringe expression was detected in the anterior neural plate of early neurulae, where it resolved into a series of segmental patches by the mid-neurulae stage. No AmphiFringe transcripts were detected in the mesoderm. Based on these observations, we propose a model depicting a successive recruitment of Fringe in the maintenance then regulation of segmentation during vertebrate evolution.

Composition, color, and texture of Thai indigenous and broiler chicken muscles

Chemical compositions and physical properties of mixed-sex Thai indigenous (Gallus domesticus) and broiler (commercial breed, CP707) chicken biceps femoris and pectoralis muscles were determined. Indigenous chicken muscles contained higher protein contents but lower fat and ash contents compared to broiler muscles (P < 0.001). The amino acid profile of the indigenous chicken muscles was similar to that of the broiler muscles except they were slightly richer in glutamic acid (P < 0.05). The indigenous chicken muscles contained more saturated and less polyunsaturated fatty acids than the broiler muscles. There were no differences in the monounsaturated fatty acid contents between the breeds. The total collagen contents of indigenous pectoralis and biceps femoris muscles were 5.09 and 12.85 mg/g, respectively, which were higher than those found in broiler pectoralis (3.86 mg/g) and biceps femoris muscles (8.70 mg/g) (P < 0.001). Soluble collagen contents were lower for indigenous pectoralis and biceps femoris muscles, 22.16 vs. 31.38% and 26.06 vs. 33.87%, respectively. The CIE system values of lightness (L*), redness (a*), and yellowness (b*) of indigenous chicken muscles were higher than those of broiler muscles. The shear values of indigenous chicken muscles either raw or cooked were higher than those of broiler muscles (P < 0.05). After cooking, the shear values decreased for broiler biceps femoris and pectoralis muscles (P < 0.05), whereas no change was observed for indigenous chicken biceps femoris muscle (P > 0.05). Shear values increased for indigenous chicken pectoralis muscle (P < 0.05).

Effect of heat treatment on the antioxidant activity, color, and free phenolic acid profile of malt

Green malt was kilned at 95 degrees C following two regimens: a standard regimen (SKR) and a rapid regimen (RKR). Both resulting malts were treated further in a tray dryer heated to 120 degrees C, as was green malt previously dried to 65 degrees C (TDR). Each regimen was monitored by determining the color, antioxidant activity (by both ABTS(center dot+) and FRAP methods), and polyphenolic profile. SKR and RKR malts exhibited decreased L* and increased b* values above approximately 80 degrees C. TDR malts changed significantly less, and color did not develop until 110 degrees C, implying that different chemical reactions lead to color in those malts. Antioxidant activity increased progressively with each regimen, although with TDR malts this became significant only at 110-120 degrees C. The RKR malt ABTS(center dot+) values were higher than those of the SKR malt. The main phenolics, that is, ferulic, p-coumaric, and vanillic acids, were monitored throughout heating. Ferulic acid levels increased upon heating to 80 degrees C for SKR and to 70 degrees C for RKR, with subsequent decreases. However, the levels for TDR malts did not increase significantly. The increase in free phenolics early in kilning could be due to enzymatic release of bound phenolics and/or easier extractability due to changes in the matrix. The differences between the kilning regimens used suggest that further modification of the regimens could lead to greater release of bound phenolics with consequent beneficial effects on flavor stability in beer and, more generally, on human health.

Texture segmentation in Williams syndrome

Williams syndrome (WS) is a developmental disorder in which visuo-spatial cognition is poor relative to verbal ability. At the level of visuo-spatial perception, individuals with WS can perceive both the local and global aspects of an image. However, the manner in which local elements are integrated into a global whole is atypical, with relative strengths in integration by luminance, closure, and alignment compared to shape, orientation and proximity. The present study investigated the manner in which global images are segmented into local parts. Segmentation by seven gestalt principles was investigated: proximity, shape, luminance, orientation, closure, size (and alignment: Experiment I only). Participants were presented with uniform texture squares and asked to detect the presence of a discrepant patch (Experiment 1) or to identify the form of a discrepant patch as a capital E or H (Experiment 2). In Experiment 1, the pattern and level of performance of the WS group did not differ from that of typically developing controls, and was commensurate with the general level of non-verbal ability observed in WS. These results were replicated in Experiment 2, with the exception of segmentation by proximity, where individuals with WS demonstrated superior performance relative to the remaining segmentation types. Overall, the results suggest that, despite some atypical aspects of visuo-spatial perception in WS, the ability to segment a global form into parts is broadly typical in this population. In turn, this informs predictions of brain function in WS, particularly areas V1 and V4. (c) 2006 Elsevier Ltd. All rights reserved.

Unsupervised segmentation using Gabor wavelets and statistical features in LIDAR data analysis

In this paper, we address issues in segmentation Of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contain 2.5 dimensional (2.5D) terrain surface height information, e.g. houses, vegetation, flat field, river, basin, etc. Our aim in this paper is to segment ground (flat field)from non-ground (houses and high vegetation) in hilly urban areas. By projecting the 2.5D data onto a surface, we obtain a texture map as a grey-level image. Based on the image, Gabor wavelet filters are applied to generate Gabor wavelet features. These features are then grouped into various windows. Among these windows, a combination of their first and second order of statistics is used as a measure to determine the surface properties. The test results have shown that ground areas can successfully be segmented from LIDAR data. Most buildings and high vegetation can be detected. In addition, Gabor wavelet transform can partially remove hill or slope effects in the original data by tuning Gabor parameters.