Edge-based connected component approach for skew correction of complex document images

Skew correction of complex document images is a difficult task. We propose an edge-based connected component approach for robust skew correction of documents with complex layout and content. The algorithm essentially consists of two steps - an 'initialization' step to determine the image orientation from the centroids of the connected components and a 'search' step to find the actual skew of the image. During initialization, we choose two different sets of points regularly spaced across the the image, one from the left to right and the other from top to bottom. The image orientation is determined from the slope between the two succesive nearest neighbors of each of the points in the chosen set. The search step finds succesive nearest neighbors that satisfy the parameters obtained in the initialization step. The final skew is determined from the slopes obtained in the 'search' step. Unlike other connected component based methods, the proposed method does not require any binarization step that generally precedes connected component analysis. The method works well for scanned documents with complex layout of any skew with a precision of 0.5 degrees.

Entropy based Skew correction of document images

The document images that are fed into an Optical Character Recognition system, might be skewed. This could be due to improper feeding of the document into the scanner or may be due to a faulty scanner. In this paper, we propose a skew detection and correction method for document images. We make use of the inherent randomness in the Horizontal Projection profiles of a text block image, as the skew of the image varies. The proposed algorithm has proved to be very robust and time efficient. The entire process takes less than a second on a 2.4 GHz Pentium IV PC.

Eye-view: A retinal image acquisition system

This paper presents a low cost but high resolution retinal image acquisition system of the human eye. The images acquired by a CMOS image sensor are communicated through the Universal Serial Bus (USB) interface to a personal computer for viewing and further processing. The image acquisition time was estimated to be 2.5 seconds. This system can also be used in telemedicine applications.

Formation of ω-Al7Cu2Fe phase during laser processing of quasicrystal-forming Al-Cu-Fe alloy

The formation of an ω-Al7Cu2Fe phase during laser cladding of quasicrystal-forming Al65Cu23.3Fe11.7 alloy on a pure aluminium substrate is reported. This phase is found to nucleate at the periphery of primary icosahedral-phase particles. A large number of ω-phase particles form an envelope around the icosahedral phase. On the outer side, they form an interface with an agr-Al solid solution. Detailed transmission electron microscopic observations show that the ω phase exhibits an orientation relationship with the icosahedral phase. Analysis of experimental results suggests that the ω phase forms by precipitation on an icosahedral phase by heterogeneous nucleation and grows into the aluminium-rich melt until supersaturation is exhausted. The microstructural observations are explained in terms of available models of phase transformations.

Hot deformation behaviour of Mg–3Al alloy—A study using processing map

The hot deformation behaviour of Mg–3Al alloy has been studied using the processing-map technique. Compression tests were conducted in the temperature range 250–550 °C and strain rate range 3 × 10−4 to 102 s−1 and the flow stress data obtained from the tests were used to develop the processing map. The various domains in the map corresponding to different dissipative characteristics have been identified as follows: (i) grain boundary sliding (GBS) domain accommodated by slip controlled by grain boundary diffusion at slow strain-rates (<10−3 s−1) in the temperature range from 350 to 450 °C, (ii) two different dynamic recrystallization (DRX) domains with a peak efficiency of 42% at 550 °C/10−1 s−1 and 425 °C/102 s−1 governed by stress-assisted cross-slip and thermally activated climb as the respective rate controlling mechanisms and (iii) dynamic recovery (DRV) domain below 300 °C in the intermediate strain rate range from 3 × 10−2 to 3 × 10−1 s−1. The regimes of flow instability have also been delineated in the processing map using an instability criterion. Adiabatic shear banding at higher strain rates (>101 s−1) and solute drag by substitutional Al atoms at intermediate strain rates (3 × 10−2 to 3 × 10−1 s−1) in the temperature range (350–450 °C) are responsible for flow instability. The relevance of these mechanisms with reference to hot working practice of the material has been indicated. The processing maps of Mg–3Al alloy and as-cast Mg have been compared qualitatively to elucidate the effect of alloying with aluminum on the deformation behaviour of magnesium.

Low-Temperature Processing of ZrB2-ZrC Composites by Reactive Hot Pressing

Dense ZrB2-ZrC and ZrB2-ZrC x∼0.67 composites have been produced by reactive hot pressing (RHP) of stoichiometric and nonstoichiometric mixtures of Zr and B4C powders at 40 MPa and temperatures up to 1600 °C for 30 minutes. The role of Ni addition on reaction kinetics and densification of the composites has been studied. Composites of ∼97 pct relative density (RD) have been produced with the stoichiometric mixture at 1600 °C, while the composite with ∼99 pct RD has been obtained with excess Zr at 1200 °C, suggesting the formation of carbon deficient ZrC x that significantly aids densification by plastic flow and vacancy diffusion mechanism. Stoichiometric and nonstoichiometric composites have a hardness of ∼20 GPa. The grain sizes of ZrB2 and ZrC x∼0.67 are ∼0.6 and 0.4 μm, respectively, which are finer than those reported in the literature.

Mesh Processing for Computerized Facial Anthropometry

Understanding of the shape and size of different features of the human body from scanned data is necessary for automated design and evaluation of product ergonomics. In this paper, a computational framework is presented for automatic detection and recognition of important facial feature regions, from scanned head and shoulder polyhedral models. A noise tolerant methodology is proposed using discrete curvature computations, band-pass filtering, and morphological operations for isolation of the primary feature regions of the face, namely, the eyes, nose, and mouth. Spatial disposition of the critical points of these isolated feature regions is analyzed for the recognition of these critical points as the standard landmarks associated with the primary facial features. A number of clinically identified landmarks lie on the facial midline. An efficient algorithm for detection and processing of the midline, using a point sampling technique, is also presented. The results obtained using data of more than 20 subjects are verified through visualization and physical measurements. A color based and triangle skewness based schemes for isolation of geometrically nonprominent features and ear region are also presented. [DOI: 10.1115/1.3330420]

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

Minimizing total weighted tardiness on a batch-processing machine with non-agreeable release times and due dates

This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time.

Monobath Processing For Holography

One of the problems encountered when photographic emulsions are used as the recording medium in holography is the appreciable time delay before the reconstruction can be viewed. This is largely due to the number of steps involved in processing and can be annoying in many applications.

Resolving Ambiguities in Confused Online Tamil Characters with Post Processing Algorithms

This paper addresses the problem of resolving ambiguities in frequently confused online Tamil character pairs by employing script specific algorithms as a post classification step. Robust structural cues and temporal information of the preprocessed character are extensively utilized in the design of these algorithms. The methods are quite robust in automatically extracting the discriminative sub-strokes of confused characters for further analysis. Experimental validation on the IWFHR Database indicates error rates of less than 3 % for the confused characters. Thus, these post processing steps have a good potential to improve the performance of online Tamil handwritten character recognition.

Polymer composite/nanocomposite processing and its effect on the electrical properties

One of the biggest challenges when considering polymer nanocomposites for electrical insulation applications lies in determining their electrical properties accurately, which in turn depend on several factors, primary being dispersion of particles in the polymer matrix. With this background, this paper reports an experimental study to understand the effects of different processing techniques on the dispersion of filler particles in the polymer matrix and their related effect on the dielectric properties of the composites. Polymer composite and nanocomposite samples for the study were prepared by mixing 10% by weight of commercially available TiO2 particles of two different sizes in epoxy using different processing methods. A considerable effect of the composite processing method could be seen in the dielectric properties of nanocomposites.