Rajneesh Kumar Srivastava

Photoluminescence and photoconductivity of ZnS:Mn2+ nanoparticles synthesized via co-precipitation method

Mn(2+) doped ZnS nanoparticles are characterized using UV-vis, photoluminescence and photoconductivity studies. The size of Mn(2+) doped ZnS NPs is estimated to be 2-4nm by X-ray diffraction. UV-vis spectra show a blue shift in absorption edge as compared to bulk counterpart. Photoluminescence spectra indicate that orange luminescence varies with Mn(2+) concentration. The Mn(2+) doped ZnS nanoparticles are found to be photosensitive. The doping of Mn(2+) ions improves the photosensitivity of the ZnS nanoparticles system. The time-resolved rise and decay of photocurrent indicate anomalous behavior during steady state illumination.

Photoluminescence and photoconductive characteristics of hydrothermally synthesized ZnO nanoparticles

In the present paper, ZnO nanoparticles (NPs) with particle size of 20–50 nm have been synthesized by hydrothermal method. UV-visible absorption spectra of ZnO nanoparticles show absorption edge at 372 nm, which is blue-shifted as compared to bulk ZnO. Photoluminescence (PL) and photoconductive device characteristics, including field response, light intensity response, rise and decay time response, and spectral response have been studied systematically. The photoluminescence spectra of these ZnO nanoparticles exhibited different emission peaks at 396 nm, 416 nm, 445 nm, 481 nm, and 524 nm. The photoconductivity spectra of ZnO nanoparticles are studied in the UV-visible spectral region (366–691 nm). In spectral response curve of ZnO NPs, the wavelength dependence of the photocurrent is very close to the absorption and photoluminescence spectra. The photo generated current, Ipc = (Itotal - Idark) and dark current Idc varies according to the power law with the applied field IpcαVr and with the intensity of illumination IpcαILr, due to the defect related mechanism including both recombination centers and traps. The ZnO NPs is found to have deep trap of 0.96 eV, very close to green band emission. The photo and dark conductivities of ZnO NPs have been measured using thick film of powder without any binder.

Photoconductivity and photoluminescence of ZnO nanoparticles synthesized via co-precipitation method

Photoconductivity and photoluminescence studies of ZnO nanoparticles (NPs) synthesized by co-precipitation method capped with thioglycerol are carried out. The effect of annealing at 300°C is also studied. The transmission electron micrograph (TEM) and X-ray diffraction (XRD) pattern confirm the hexagonal wurtzite structure of ZnO nanoparticles. The UV-vis absorption spectrum of ZnO NPs shows blue shift of absorption peak as compared to bulk ZnO. The photoluminescence (PL) spectra of as-synthesized ZnO NPs show band edge emission as well as blue-green emission. After annealing band edge emission is quenched. Photocurrent is found to vary super linearly at high voltage for both as-synthesized as well as annealed ZnO NPs. Time resolved rise and decay photocurrent spectra are found to exhibit anomalous photoconductivity for as-synthesized as well as annealed ZnO NPs wherein the photocurrent decreases even during steady illumination.

Moving object segmentation in Daubechies complex wavelet domain

Motion segmentation is a crucial step in video analysis and is associated with a number of computer vision applications. This paper introduces a new method for segmentation of moving object which is based on double change detection technique applied on Daubechies complex wavelet coefficients of three consecutive frames. Daubechies complex wavelet transform for segmentation of moving object has been chosen as it is approximate shift invariant and has a better directional selectivity as compared to real valued wavelet transform. Double change detection technique is used to obtain video object plane by inter-frame difference of three consecutive frames. Double change detection technique also provides automatic detection of appearance of new objects. The proposed method does not require any other parameter except Daubechies complex wavelet coefficients. Results of the proposed method for segmentation of moving objects are compared with results of other state-of-the-art methods in terms of visual performance and a number of quantitative performance metrics viz. Misclassification Penalty, Relative Foreground Area Measure, Pixel Classification Based Measure, Normalized Absolute Error, and Percentage of Correct Classification. The proposed method is found to have high degree of segmentation accuracy than the other state-of-the-art methods.

Single change detection-based moving object segmentation by using Daubechies complex wavelet transform

Research in motion analysis is a challenging field and it has a variety of video surveillance applications. For any video surveillance application, background detection and removal plays an important role in segmentation of the moving objects. This study proposes a new method for segmentation of the moving object, which is based on single change detection applied on Daubechies complex wavelet coefficients of two consecutive frames. The authors have chosen Daubechies complex wavelet transform as it is shift invariant and has a better directional selectivity as compared with real-valued wavelet transforms. Single change detection is a method to obtain video object plane by inter-frame difference of two consecutive frames, and it provides automatic detection of appearances of new objects. The proposed method does not require any other parameter except wavelet coefficients. Segmentation results of the moving objects after applying the proposed method are compared with those obtained after applying other spatial and wavelet domain segmentation methods in terms of visual performance and a number of quantitative measures viz misclassification penalty, relative position-based measure, structural content, normalised absolute error and average difference and the proposed method is found better than the other methods.

Effect of Indium Doping and Annealing on Photoconducting Property of Wurtzite type CdS

In this paper we observed the effect of doping and annealing on the dark current and anomalous photoconducting behavior of hexagonal wurtzite CdS, synthesized by solid state reaction method. Undoped CdS sample shows higher anomalous behavior in photoconductivity as well as contains larger dark current of 19 nA. With the doping of Indium in CdS, dark current decreases from 19 nA to 1 nA but the anomalous behavior is not completely removed. While, after annealing at 150°C for four hour, indium doped CdS sample shows good switching property with rise and decay time of 360 ± 10 & 322 ± 6 seconds respectively. The anomalous photoconducting behavior is completely removed from annealed sample. X-ray diffraction patterns confirm the existence of hexagonal wurtzite phase of indium doped and undoped CdS samples while energy dispersion X-ray spectrum exhibits the elemental presence of cadmium, indium & sulfur in the indium doped sample. UV-Visible absorption spectra show the blue shift in absorption edge on indium doping from 475 nm to 425 nm in comparison to undoped sample. Photoluminescence spectra confirm the indium doping and reveal that annealed CdS sample has lesser defects among other samples due to which annealed sample has best switching performance.

Moving shadow detection and removal – a wavelet transform based approach

Shadow detection and removal is an important problem in computer vision. The real challenge in moving shadow detection and removal is to classify moving shadow points which are many times misclassified as moving object points in a video sequences. Various shadow detection and removal algorithms have been proposed for images but only a few works have been done for moving objects. In this study, a novel method for shadow detection and removal is proposed using discrete wavelet transform (DWT). The authors have used DWT because of its multi-resolution property that decomposes an image into four different bands without loss of the spatial information. For detection and removal of shadow, they have proposed a new threshold in the form of relative standard deviation. The value of threshold is automatically determined and does not require any supervised learning or manual calibration. The proposed method is flexible and depends on only one parameter, namely, wavelet coefficients. Results of shadow detection and removal from moving object after applying the proposed method are compared with the results of other state-of-the-art methods in terms of visual performance and a number of quantitative performance parameters. The proposed method is found to be better and more robust than other methods.

An effective local feature descriptor for object detection in real scenes

In this study, we advocate the importance of robust local features that allow object form to be distinguished from other objects for detection purpose. We start from the grid of Histogram of oriented gradients (HOG) and integrate Scale Invariant Feature Transform (SIFT) within them. In HOG features an objects appearance is detected by the distribution of local intensity gradients or edge directions for different cells. In the proposed method we have computed the SIFT despite of computing intensity gradients for these cells. In this way, the proposed approach does not only provide more significant information than just providing intensity gradients but also proves to deal with following challenges: (i) scale invariance; (ii) rotation invariance; (iii) change in illumination; and (iv) change in view points. With qualitative and quantitative experimental evaluation on standard INRIA dataset, we have compared the proposed method with other state of the art object detection methods and demonstrated better performance over them.

Study of dark-conductivity and photoconductivity of ZnO nano structures synthesized by thermal decomposition of zinc oxalate

In the present work, zinc oxalate [ZnC2O4·2H2O] was used as precursor to prepare zinc oxide nano structures by thermal decomposition. Its photoconductivity and dark-conductivity properties have been studied in air as well as in vacuum. Voltage dependence of photocurrent and dark-current has been observed at room temperature in air under UV-vis illumination and is found as superlinear in nature. Rise and decay curve in air exhibits anomalous behavior wherein the photocurrent decreases even during steady illumination. In vacuum, the rise of photocurrent becomes slow and prolonged.

Automatic multiple human detection and tracking for visual surveillance system

Object Tracking is an important task in video processing because of its variety of applications in visual surveillance, human activity monitoring and recognition, traffic flow management etc. Multiple object detection and tracking in outdoor environment is a challenging task because of the problems raised by poor lighting conditions, variation in poses of human object, shape, size, clothing, etc. This paper proposes a novel technique for detection and tracking of multiple human objects in a video. A classifier is trained for object detection using Haar-like features from training image set. Human objects are detected with help of this trained detector and are tracked using particle filter. The experimental results show that the proposed technique can detect and track multiple humans in a video adequately fast in the presence of poor lighting conditions, variation in poses of human objects, shape, size, clothing etc. and the technique can handle varying number of human objects in a video at various points of time.