Thinning-free Polygonal Approximation of Thick Digital Curves Using Cellular Envelope

Since the inception of successful rasterization of curves and objects in the digital space, several algorithms have been proposed for approximating a given digital curve. All these algorithms, however, resort to thinning as preprocessing before approximating a digital curve with changing thickness. Described in this paper is a novel thinning-free algorithm for polygonal approximation of an arbitrarily thick digital curve, using the concept of "cellular envelope", which is newly introduced in this paper. The cellular envelope, defined as the smallest set of cells containing the given curve, and hence bounded by two tightest (inner and outer) isothetic polygons, is constructed using a combinatorial technique. This envelope, in turn, is analyzed to determine a polygonal approximation of the curve as a sequence of cells using certain attributes of digital straightness. Since a real-world curve=curve-shaped object with varying thickness, unexpected disconnectedness, noisy information, etc., is unsuitable for the existing algorithms on polygonal approximation, the curve is encapsulated by the cellular envelope to enable the polygonal approximation. Owing to the implicit Euclidean-free metrics and combinatorial properties prevailing in the cellular plane, implementation of the proposed algorithm involves primitive integer operations only, leading to fast execution of the algorithm. Experimental results that include output polygons for different values of the approximation parameter corresponding to several real-world digital curves, a couple of measures on the quality of approximation, comparative results related with two other well-referred algorithms, and CPU times, have been presented to demonstrate the elegance and efficacy of the proposed algorithm

Multilayered and Chemiresistive Thin and Thick Film Gas Sensors for Air Quality Monitoring

Selective detection of gases such as nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxide (CO2), and various volatile organic components (VOCs) is necessary for air quality monitoring. Detection of hydrogen (H2) is equally important as it is a flammable gas and poses serious threat of explosion when exposed to oxygen gas. We have studied the sensing characteristics of these gases using thin film deposited by chemical solution deposition as well as relatively thicker films deposited by atmospheric plasma spray (APS) process. The chapter starts with the sensing mechanism of chemiresistive sensors followed by the definition of gas sensing parameters. Subsequently, we have demonstrated selective NO2 sensing characteristics of zinc oxide-graphene (ZnO-G) multilayered thin film followed by CO and H2 sensing characteristics of ZnO thin film and SnO2 thick film. Cross-sensitivity among CO and H2 gases has been addressed through the analysis of conductance transients with the determination of activation energy, Ea, and heat of adsorption, Q. The concepts of reversible and irreversible sensing have also been discussed in relation to CO and H2 gases. CO2 sensing characteristics of LaFe0.8Co0.2O3 (LFCO)-ZnO thin film have been elucidated. Interference from CO has been addressed with principal component analyses and the ascertaining of Ea and Q values. Additionally, the variation of response with temperature for each gas was simulated to determine distinct parameters for the individual gases. Further, VOC sensing characteristics of copper oxide (CuO) thin film and WO3-SnO2 thick film were investigated. Principal component analysis was performed to discriminate the gases in CuO thin film. The interaction of WO3-SnO2 thick film with various VOCs was found to obey the Freundlich adsorption isotherm based on which Ea and Q values were determined

Prevention and Therapy of Hepatocellular Carcinoma by Vaccination with TM4SF5 Epitope-CpG-DNA-Liposome Complex without Carriers

Although peptide vaccines have been actively studied in various animal models, their efficacy in treatment is limited. To improve the efficacy of peptide vaccines, we previously formulated an efficacious peptide vaccine without carriers using the natural phosphodiester bond CpG-DNA and a special liposome complex (Lipoplex(O)). Here, we show that immunization of mice with a complex consisting of peptide and Lipoplex(O) without carriers significantly induces peptide-specific IgG2a production in a CD4+ cells- and Th1 differentiation-dependent manner. The transmembrane 4 superfamily member 5 protein (TM4SF5) has gained attention as a target for hepatocellular carcinoma (HCC) therapy because it induces uncontrolled growth of human HCC cells via the loss of contact inhibition. Monoclonal antibodies specific to an epitope of human TM4SF5 (hTM4SF5R2-3) can recognize native mouse TM4SF5 and induce functional effects on mouse cancer cells. Pre-immunization with a complex of the hTM4SF5R2-3 epitope and Lipoplex(O) had prophylactic effects against tumor formation by HCC cells implanted in an mouse tumor model. Furthermore, therapeutic effects were revealed regarding the growth of HCC when the vaccine was injected into mice after tumor formation. These results suggest that our improved peptide vaccine technology provides a novel prophylaxis measure as well as therapy for HCC patients with TM4SF5-positive tumors

Determination of minutiae scores for fingerprint image applications

Many Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching. Minutiae are the terminations and bifurcations of the ridge lines in a fingerprint image. A gray-scale fingerprint image that has undergone binarization, followed by thinning, in order to extract the minutiae, may contain hundreds of minutiae, all of which are not so vivid and obvious in the original image. Thus, the set of minutiae that are well-defined and more prominent than the rest should be given higher relevance and importance in the process of minutiae matching. In this work, a gray-scale fingerprint image is first preprocessed to produce a thinned binary image. Next, a method to assign a score value to each of the extracted minutiae i