Modeling of woven fabric structures based on fourier image analysis

INDMF Based Regularity Calculation Method and Its Application in the Recognition of Typical Loess Landforms

The topographical morphology of the loess landform on the Loess Plateau exhibits remarkable textural features at different spatial scales. However, existing topographic texture analysis studies on the Loess Plateau are usually dominated by statistical characteristics and are missing structural characteristics. At the same time, there is a lack of regularity calculation methods for DEM digital terrain analysis. Taking the Loess Plateau as the study area, a regularity calculation method based on the improved normalized distance matching function (INDMF) is proposed and applied to the classification of a loess landform. The regularity calculation method used in this study (INDMF regularity) mainly includes two key steps. Step 1 calculates the INDMF sequence value and the peak and valley values for the terrain data. Step 2 calculates the significant peak and valley, constructs the significant peak and valley sequences, and then obtains the regularity using the normalised ratio value. The experimental results show that the proposed method has good anti-interference ability and can effectively extract the regularity of the main landform unit. Compared with previous methods, adding structural features (i.e., INDMF regularity) can effectively distinguish loess hill and loess ridge in the hilly and gully region. For the loess hill and loess ridge, the recognition rates of the proposed method are 84.62% and 92.86%, respectively. Combined with the existing topographic characteristics, the proposed INDMF regularity is a topographic structure feature extraction method that can effectively discriminate between loess hill and loess ridge areas on the Loess Plateau.

A microscale camera using direct Fourier-domain scene capture

We demonstrate a chip-scale (<1 mm(2)) sensor, the Planar Fourier Capture Array (PFCA), capable of imaging the far field without any off-chip optics. The PFCA consists of an array of angle-sensitive pixels manufactured in a standard semiconductor process, each of which reports one component of a spatial two-dimensional (2D) Fourier transform of the local light field. Thus, the sensor directly captures 2D Fourier transforms of scenes. The effective resolution of our prototype is approximately 400 pixels.

Weave-repeat identification by structural analysis of fabric images

Two descriptions of the image of a web structure, a convolution model and an additive model, in both the spatial and frequency domains, are combined in the design of a method to extract information about the fabric structure by image analysis. The method allows the extraction of the conventional and also the minimal weave repeats, their size in terms of number of threads, their interlacing patterns, and their patterns of repetition. It is applicable to fabrics with square and nonsquare conventional weave repeat. Experimental results with image of real samples are presented and discussed.