Dynamic Background Updating for Lightweight Moving Object Detection

Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a simple moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Microwave Sintering and Its Application on Cemented Carbides

Cemented carbides, owing to their excellent mechanical properties, have been of immense interest in the field of hard materials for the past few decades. A number of processing techniques have been developed to obtain high quality carbide tools, with a wide range of grain size depending on the application and requirements. Microwave sintering is one of the heating processes, which has been used to prepare a wide range of materials including ceramics. A deep understanding of microwave sintering and its contribution towards control of grain growth and on deformation of the resulting carbide materials requires further studies and attention. In addition, the effect of binder materials and their behavior during microwave sintering is another area that requires clear understanding. This review aims to focus on microwave sintering, providing information of how the process works and what type of materials it is best suited for. In addition, a closer look at some microwave sintered Tungsten Carbide-Cobalt samples will be taken and discussed, highlighting some of the key issues and challenges faced in this research area.

Bacteriological Quality of Commercially Prepared Fermented Ogi (Akamu) Sold in Some Parts of South Eastern Nigeria

Food poisoning and infection by bacteria are of public health significance to both developing and developed countries. Samples of ogi (akamu) prepared from white and yellow variety of maize sold in Uturu and Okigwe were analyzed together with the laboratory prepared ogi for bacterial quality using the standard microbiological methods. The analyses showed that both white and yellow variety had total bacterial counts (cfu/g) of 4.0 ×107 and 3.9 x 107 for the laboratory prepared ogi while the commercial ogi had 5.2 x 107 and 4.9 x107, 4.9 x107 and 4.5 x107, 5.4 x107 and 5.0 x107 for Eke-Okigwe, Up-gate and Nkwo-Achara market respectively. The Staphylococcal counts ranged from 2.0 x 102 to 5.0 x102 and 1.0 x 102 to 4.0 x102 for the white and yellow variety from the different markets while Staphylococcal growth was not recorded on the laboratory prepared ogi. The laboratory prepared ogi had no Coliform growth while the commercially prepared ogi had counts of 0.5 x103 to 1.6 x 103 for white variety and 0.3 x 103 to 1.1 x103 for yellow variety respectively. The Lactic acid bacterial count of 3.5x106 and 3.0x106 was recorded for the laboratory ogi while the commercially prepared ogi ranged from 3.2x106 to 4.2x106 (white variety) and 3.0 x106 to 3.9 x106 (yellow). The presence of bacteria isolates from the commercial and laboratory fermented ogi showed that Lactobacillus sp, Leuconostoc sp and Citrobacter sp were present in all the samples, Micrococcus sp and Klebsiella sp were isolated from Eke- Okigwe and ABSU-up-gate markets varieties respectively, E. coli and Staphylococcus sp were present in Eke-Okigwe and Nkwo- Achara markets while Salmonella sp were isolated from the three markets. Hence, there are chances of contracting food borne diseases from commercially prepared ogi. Therefore, there is the need for sanitary measures in the production of fermented cereals so as to minimize the rate of food borne pathogens during processing and storage.

Plasma Lipid Profiles and Atherogenic Indices of Rats Fed Raw and Processed Jack Fruit (Artocarpus heterophyllus) Seeds Diets at Different Concentrations

The effect of processing on plasma lipid profile and atherogenic indices of rats fed Artocarpus heterophyllus seed diets at different concentrations were investigated. Fifty five rats were used for this study, they were divided into eleven groups of five rats each (one control group and ten test groups), the test groups were fed raw, boiled, roasted, fermented and soaked diets at 10% and 40% concentrations. The study lasted for thirty five days. The diets led to significant decrease (p

Rheological Modeling for Shape-Memory Thermoplastic Polymers

This paper presents a rheological model for producing shape-memory thermoplastic polymers. Shape-memory occurs as a result of internal rearrangement of the structural elements of a polymer. A non-linear viscoelastic model was developed that allows qualitative and quantitative prediction of the stress-strain behavior of shape-memory polymers during heating. This research was done to develop a technique to determine the maximum possible change in size of shape-memory products during heating. The rheological model used in this work was particularly suitable for defining process parameters and constructive parameters of the processing equipment.

Identification of Healthy and BSR-Infected Oil Palm Trees Using Color Indices

Most of the oil palm plantations have been threatened by Basal Stem Rot (BSR) disease which causes serious economic impact. This study was conducted to identify the healthy and BSRinfected oil palm tree using thirteen color indices. Multispectral and thermal camera was used to capture 216 images of the leaves taken from frond number 1, 9 and 17. Indices of normalized difference vegetation index (NDVI), red (R), green (G), blue (B), near infrared (NIR), green – blue (GB), green/blue (G/B), green – red (GR), green/red (G/R), hue (H), saturation (S), intensity (I) and thermal index (T) were used. From this study, it can be concluded that G index taken from frond number 9 is the best index to differentiate between the healthy and BSR-infected oil palm trees. It not only gave high value of correlation coefficient (R=-0.962), but also high value of separation between healthy and BSR-infected oil palm tree. Furthermore, power and S model developed using G index gave the highest R2 value which is 0.985.

A Background Subtraction Based Moving Object Detection around the Host Vehicle

In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added. We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Applying Kinect on the Development of a Customized 3D Mannequin

In the field of fashion design, 3D Mannequin is a kind of assisting tool which could rapidly realize the design concepts. While the concept of 3D Mannequin is applied to the computer added fashion design, it will connect with the development and the application of design platform and system. Thus, the situation mentioned above revealed a truth that it is very critical to develop a module of 3D Mannequin which would correspond with the necessity of fashion design. This research proposes a concrete plan that developing and constructing a system of 3D Mannequin with Kinect. In the content, ergonomic measurements of objective human features could be attained real-time through the implement with depth camera of Kinect, and then the mesh morphing can be implemented through transformed the locations of the control-points on the model by inputting those ergonomic data to get an exclusive 3D mannequin model. In the proposed methodology, after the scanned points from the Kinect are revised for accuracy and smoothening, a complete human feature would be reconstructed by the ICP algorithm with the method of image processing. Also, the objective human feature could be recognized to analyze and get real measurements. Furthermore, the data of ergonomic measurements could be applied to shape morphing for the division of 3D Mannequin reconstructed by feature curves. Due to a standardized and customer-oriented 3D Mannequin would be generated by the implement of subdivision, the research could be applied to the fashion design or the presentation and display of 3D virtual clothes. In order to examine the practicality of research structure, a system of 3D Mannequin would be constructed with JAVA program in this study. Through the revision of experiments the practicability-contained research result would come out.

3D Objects Indexing with a Direct and Analytical Method for Calculating the Spherical Harmonics Coefficients

In this paper, we propose a new method for threedimensional object indexing based on D.A.M.C-S.H.C descriptor (Direct and Analytical Method for Calculating the Spherical Harmonics Coefficients). For this end, we propose a direct calculation of the coefficients of spherical harmonics with perfect precision. The aims of the method are to minimize, the processing time on the 3D objects database and the searching time of similar objects to a request object. Firstly we start by defining the new descriptor using a new division of 3-D object in a sphere. Then we define a new distance which will be tested and prove his efficiency in the search for similar objects in the database in which we have objects with very various and important size.

Fuzzy Inference System Based Unhealthy Region Classification in Plant Leaf Image

In addition to environmental parameters like rain, temperature diseases on crop is a major factor which affects production quality & quantity of crop yield. Hence disease management is a key issue in agriculture. For the management of disease, it needs to be detected at early stage. So, treat it properly & control spread of the disease. Now a day, it is possible to use the images of diseased leaf to detect the type of disease by using image processing techniques. This can be achieved by extracting features from the images which can be further used with classification algorithms or content based image retrieval systems. In this paper, color image is used to extract the features such as mean and standard deviation after the process of region cropping. The selected features are taken from the cropped image with different image size samples. Then, the extracted features are taken in to the account for classification using Fuzzy Inference System (FIS).

Analysis of Surface Hardness, Surface Roughness, and Near Surface Microstructure of AISI 4140 Steel Worked with Turn-Assisted Deep Cold Rolling Process

In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the surface hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor hobson talysurf tester, micro vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer. 

Achieving Sustainable Agriculture with Treated Municipal Wastewater

A pilot field study was conducted at the Jagjeetpur Municipal Sewage treatment plant situated in the Haridwar town in Uttarakhand state, India. The objectives of the present study were to study the effect of treated wastewater on the production of various paddy varieties (Sharbati, PR-114, PB-1, Menaka, PB1121 and PB 1509) and the emission of GHG gases (CO2, CH4 and N2O) as compared to the same varieties grown in the control plots irrigated with fresh water. Of late, the concept of water footprint assessment has emerged, which explains enumeration of various types of water footprints of an agricultural entity from its production to processing stages. Paddy, the most water demanding staple crop of Uttarakhand state, displayed a high green water footprint value of 2474.12 m3/ Ton. Most of the wastewater irrigated varieties displayed up to 6% increase in production, except Menaka and PB-1121, which showed a reduction in production (6% and 3% respectively), due to pest and insect infestation. The treated wastewater was observed to be rich in Nitrogen (55.94 mg/ml Nitrate), Phosphorus (54.24 mg/ml) and Potassium (9.78 mg/ml), thus rejuvenating the soil quality and not requiring any external nutritional supplements. A Percentage increase of GHG gases of irrigation with treated municipal wastewater as compared to control plots was observed as 0.4% - 8.6% (CH4), 1.1% - 9.2% (CO2), and 0.07% - 5.8% (N2O). The variety, Sharbati, displayed maximum production (5.5 ton/ha) and emerged as the most resistant variety against pests and insects. The emission values of CH4, CO2 and N2O were 729.31 mg/m2/d, 322.10 mg/m2/d and 400.21 mg/m2/d in water stagnant condition. This study highlighted a successful possibility of reuse of wastewater for non-potable purposes offering the potential for exploiting this resource that can replace or reduce the existing use of fresh water sources in agriculture sector.

Automatic Motion Trajectory Analysis for Dual Human Interaction Using Video Sequences

Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.). 

Comparison of Processing Conditions for Plasticized PVC and PVB

It is the worldwide problem that the recycled PVB is not recycled and it is wildly stored in landfills. However, PVB has similar chemical properties such as PVC. Moreover, both of these polymers are plasticized. Therefore, the study of thermal properties of plasticized PVC and the recycled PVB obtained by recycling of windshields is carried out. This work has done in order to find nondegradable processing conditions applicable for both polymers. Tested PVC contained 38% of plasticizer diisononyl phthalate (DINP) and PVB was plasticized with 28% of triethylene glycol, bis(2-ethylhexanoate) (3GO). The thermal and thermo-oxidative decomposition of both vinyl polymers are compared by calorimetric analysis and by tensile strength analysis.

A System for Analyzing and Eliciting Public Grievances Using Cache Enabled Big Data

The system for analyzing and eliciting public grievances serves its main purpose to receive and process all sorts of complaints from the public and respond to users. Due to the more number of complaint data becomes big data which is difficult to store and process. The proposed system uses HDFS to store the big data and uses MapReduce to process the big data. The concept of cache was applied in the system to provide immediate response and timely action using big data analytics. Cache enabled big data increases the response time of the system. The unstructured data provided by the users are efficiently handled through map reduce algorithm. The processing of complaints takes place in the order of the hierarchy of the authority. The drawbacks of the traditional database system used in the existing system are set forth by our system by using Cache enabled Hadoop Distributed File System. MapReduce framework codes have the possible to leak the sensitive data through computation process. We propose a system that add noise to the output of the reduce phase to avoid signaling the presence of sensitive data. If the complaints are not processed in the ample time, then automatically it is forwarded to the higher authority. Hence it ensures assurance in processing. A copy of the filed complaint is sent as a digitally signed PDF document to the user mail id which serves as a proof. The system report serves to be an essential data while making important decisions based on legislation.

Segmentation of Noisy Digital Images with Stochastic Gradient Kernel

Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.

An Efficient Clustering Technique for Copy-Paste Attack Detection

Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Screening of Congenital Heart Diseases with Fetal Phonocardiography

The paper presents a novel screening method to indicate congenital heart diseases (CHD), which otherwise could remain undetected because of their low level. Therefore, not belonging to the high-risk population, the pregnancies are not subject to the regular fetal monitoring with ultrasound echocardiography. Based on the fact that CHD is a morphological defect of the heart causing turbulent blood flow, the turbulence appears as a murmur, which can be detected by fetal phonocardiography (fPCG). The proposed method applies measurements on the maternal abdomen and from the recorded sound signal a sophisticated processing determines the fetal heart murmur. The paper describes the problems and the additional advantages of the fPCG method including the possibility of measurements at home and its combination with the prescribed regular cardiotocographic (CTG) monitoring. The proposed screening process implemented on a telemedicine system provides an enhanced safety against hidden cardiac diseases.

Contrast Enhancement of Masses in Mammograms Using Multiscale Morphology

Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other stateof- the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.

Discrete and Stationary Adaptive Sub-Band Threshold Method for Improving Image Resolution

Image Processing is a structure of Signal Processing for which the input is the image and the output is also an image or parameter of the image. Image Resolution has been frequently referred as an important aspect of an image. In Image Resolution Enhancement, images are being processed in order to obtain more enhanced resolution. To generate highly resoluted image for a low resoluted input image with high PSNR value. Stationary Wavelet Transform is used for Edge Detection and minimize the loss occurs during Downsampling. Inverse Discrete Wavelet Transform is to get highly resoluted image. Highly resoluted output is generated from the Low resolution input with high quality. Noisy input will generate output with low PSNR value. So Noisy resolution enhancement technique has been used for adaptive sub-band thresholding is used. Downsampling in each of the DWT subbands causes information loss in the respective subbands. SWT is employed to minimize this loss. Inverse Discrete wavelet transform (IDWT) is to convert the object which is downsampled using DWT into a highly resoluted object. Used Image denoising and resolution enhancement techniques will generate image with high PSNR value. Our Proposed method will improve Image Resolution and reached the optimized threshold.