A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.

Optimising memory usage in n-tuple neural networks

The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been used for a variety of tasks, the most popular being real-time pattern recognition, and they can be implemented easily in hardware as they use standard random access memories. In operation, a series of images of an object are shown to the network, each being processed suitably and effectively stored in a memory called a discriminator. Then, when another image is shown to the system, it is processed in a similar manner and the system reports whether it recognises the image; is the image sufficiently similar to one already taught? If the system is to be able to recognise and discriminate between m-objects, then it must contain m-discriminators. This can require a great deal of memory. This paper describes various ways in which memory requirements can be reduced, including a novel method for multiple discriminator n-tuple networks used for pattern recognition. By using this method, the memory normally required to handle m-objects can be used to recognise and discriminate between 2^m — 2 objects.

Auto-associative memory using n-tuple techniques

The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.

Preventing carbon contamination of optical devices for X-rays: the effect of oxygen on photon-induced dissociation of CO on platinum

Platinum is one of the most common coatings used to optimize mirror reflectivity in soft X-ray beamlines. Normal operation results in optics contamination by carbon-based molecules present in the residual vacuum of the beamlines. The reflectivity reduction induced by a carbon layer at the mirror surface is a major problem in synchrotron radiation sources. A time-dependent photoelectron spectroscopy study of the chemical reactions which take place at the Pt(111) surface under operating conditions is presented. It is shown that the carbon contamination layer growth can be stopped and reversed by low partial pressures of oxygen for optics operated in intense photon beams at liquidnitrogen temperature. For mirrors operated at room temperature the carbon contamination observed for equivalent partial pressures of CO is reduced and the effects of oxygen are observed on a long time scale.

Cloud optical and microphysical properties derived from ground-based and satellite sensors over a site in the Yangtze Delta region

Comprehensive surface-based retrievals of cloud optical and microphysical properties were made at Taihu, a highly polluted site in the central Yangtze Delta region, during a research campaign from May 2008 to December 2009. Cloud optical depth (COD), effective radius (Re), and liquid water path (LWP) were retrieved from measurements made with a suite of ground-based and spaceborne instruments, including an Analytical Spectral Devices spectroradiometer, a multi␣lter rotating shadowband radiometer, a multichannel microwave radiometer profiler, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua satellites. Retrievals from zenith radiance measurements capture better the temporal variation of cloud properties than do retrievals from hemispherical fluxes. Annual mean LWP, COD, and Re are 115.8 ± 90.8 g/m2, 28.5 ± 19.2, and 6.9 ± 4.2 microns. Over 90% of LWP values are less than 250 g/m2. Most of the COD values (>90%) fall between 5 and 60, and ~80% of Re values are less than 10 microns. Maximum (minimum) values of LWP and Re occur in summer (winter); COD is highest in winter and spring. Raining and nonraining clouds have signi␣cant differences in LWP, COD, and Re. Rainfall frequency is best correlated with LWP, followed by COD and Re. Cloud properties retrieved from multiple ground-based instruments are also compared with those from satellite retrievals. On average, relative to surface retrievals, mean differences of satellite retrievals in cloud LWP, COD, and Re were -33.6 g/m2 (-26.4%), -5.8 (-31.4%), and 2.9 ␣m (29.3%) for 11 MODIS-Terra overpasses and -43.3 g/m2 (-22.3%), -3.0 (-10.0%), and -1.3 ␣m (-12.0%) for 8 MODIS-Aqua overpasses, respectively. These discrepancies indicate that MODIS cloud products still suffer from large uncertainties in this region.

Polymorphism and optical properties in [NH4][InSe2]

The solvothermal synthesis and characterization of two indium selenides with stoichiometry [NH4][InSe2] is described. Yellow [NH4][InSe2] (1), which exhibits a layered structure, was initially prepared in an aqueous solution of trans-1,4-diaminocyclohexane, and subsequently using a concentrated ammonia solution. A red polymorph of one-dimensional character, [NH4][InSe2] (2), was obtained using 3,5-dimethylpyridine as solvent. [NH4][InSe2] (1) crystallizes in the non-centrosymmetric space group Cc (a=11.5147(6), b=11.3242(6), c=15.9969(9) Å and β=100.354(3)°). The structural motif of the layers is the In4Se10 adamantane unit, composed of four corner-linked InSe4 tetrahedra. These units are linked by their corners, forming [InSe2]− layers which are stacked back to back along the c-direction, and interspaced by [NH4]+cations. The one-dimensional polymorph, (2), crystallizes in the tetragonal space group, I4/mcm (a=8.2519(16), c=6.9059 (14) Å). This structure contains infinite chains of edge-sharing InSe4 tetrahedra separated by [NH4]+ cations.