This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
Inpainting refers to the art of restoring lost parts of image and reconstructing them based on the background information i.e Image inpainting is the process of reconstructing lost or deteriorated parts of images using information from surrounding areas. In fine art museums, inpainting of degraded paintings is traditionally carried out by professional artists and usually very time consuming.The purpose of inpainting is to reconstruct missing regions in a visually plausible manner so that it seems reasonable to the human eye. There have been several approaches proposed for the same.
This paper gives an overview of different Techniques of Image Inpainting.The proposed work includes the overview of PDE based inpainting algorithm and Texture synthesis based inpainting algorithm. This paper presents a brief survey on comparative study of these two techniques used for Image Inpainting.
In this project we have implemented a tool to inpaint selected regions from an image. Inpainting refers to the art of restoring lost parts of image and reconstructing them based on the background information. The tool provides a user interface wherein the user can open an image for inpainting, select the parts
of the image that he wants to reconstruct. The tool would then automatically inpaint the selected area according to the background information. The image can
then be saved. The inpainting in based on the exemplar based approach. The basic aim of this approach is to find examples (i.e. patches) from the image and
replace the lost data with it. Applications of this technique include the restoration of old photographs and damaged film; removal of superimposed text like
dates, subtitles etc.; and the removal of entire objects from the image like microphones or wires in special effects.
Region filling and object removal by exemplar based image inpaintingWoonghee Lee
To get rid of (an) object(s) at a picture or to restore a picture from scratches or holes, Criminisi at el. suggested an algorithm which is combied "texture synthesis" and "inpainting". I made the slide to present at a class to introduce this algorithm. I refered a slide http://bit.ly/1Ng7DNt. I wish this slide may help you to understand the algorithm. Thank you.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
A Survey on Exemplar-Based Image Inpainting Techniquesijsrd.com
Preceding paper include exemplar-based image inpainting technique give idea how to inpaint destroyed region such as Criminisi algorithm, patch shifting scheme, search region prior method. Criminsi’s and Sarawut’s patch shifting scheme needed more time to inpaint an damaged region but proposed method decrease time complexity by searching only in related region of missing portion of image.
Inpainting refers to the art of restoring lost parts of image and reconstructing them based on the background information i.e Image inpainting is the process of reconstructing lost or deteriorated parts of images using information from surrounding areas. In fine art museums, inpainting of degraded paintings is traditionally carried out by professional artists and usually very time consuming.The purpose of inpainting is to reconstruct missing regions in a visually plausible manner so that it seems reasonable to the human eye. There have been several approaches proposed for the same.
This paper gives an overview of different Techniques of Image Inpainting.The proposed work includes the overview of PDE based inpainting algorithm and Texture synthesis based inpainting algorithm. This paper presents a brief survey on comparative study of these two techniques used for Image Inpainting.
In this project we have implemented a tool to inpaint selected regions from an image. Inpainting refers to the art of restoring lost parts of image and reconstructing them based on the background information. The tool provides a user interface wherein the user can open an image for inpainting, select the parts
of the image that he wants to reconstruct. The tool would then automatically inpaint the selected area according to the background information. The image can
then be saved. The inpainting in based on the exemplar based approach. The basic aim of this approach is to find examples (i.e. patches) from the image and
replace the lost data with it. Applications of this technique include the restoration of old photographs and damaged film; removal of superimposed text like
dates, subtitles etc.; and the removal of entire objects from the image like microphones or wires in special effects.
Region filling and object removal by exemplar based image inpaintingWoonghee Lee
To get rid of (an) object(s) at a picture or to restore a picture from scratches or holes, Criminisi at el. suggested an algorithm which is combied "texture synthesis" and "inpainting". I made the slide to present at a class to introduce this algorithm. I refered a slide http://bit.ly/1Ng7DNt. I wish this slide may help you to understand the algorithm. Thank you.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
A Survey on Exemplar-Based Image Inpainting Techniquesijsrd.com
Preceding paper include exemplar-based image inpainting technique give idea how to inpaint destroyed region such as Criminisi algorithm, patch shifting scheme, search region prior method. Criminsi’s and Sarawut’s patch shifting scheme needed more time to inpaint an damaged region but proposed method decrease time complexity by searching only in related region of missing portion of image.
Comparison of Segmentation Algorithms and Estimation of Optimal Segmentation ...Pinaki Ranjan Sarkar
Recent advancement in sensor technology allows very high spatial resolution along with multiple spectral bands. There are many studies, which highlight that Object Based Image Analysis(OBIA) is more accurate than pixel-based classification for high resolution(< 2m) imagery. Image segmentation is a crucial step for OBIA and it is a very formidable task to estimate optimal parameters for segmentation as it does not have any unique solution. In this paper, we have studied different segmentation algorithms (both mono-scale and multi-scale) for different terrain categories and showed how the segmented output depends on upon various parameters. Later, we have introduced a novel method to estimate optimal segmentation parameters. The main objectives of this study are to highlight the effectiveness of presently available segmentation techniques on very high-resolution satellite data and to automate segmentation process. Pre-estimation of segmentation parameter is more practical and efficient in OBIA. Assessment of segmentation algorithms and estimation of segmentation parameters are examined based on the very high-resolution multi-spectral WorldView-3(0.3m, PAN sharpened) data.
An evaluation of two popular segmentation algorithms, the mean shift-based segmentation algorithm and a graph-based segmentation scheme. We also consider a hybrid method which combines the other two methods.
Abstract: Many applications such as robot navigation, defense, medical and remote sensing performvarious processing tasks, which can be performed more easily when all objects in different images of the same scene are combined into a single fused image. In this paper, we propose a fast and effective method for image fusion. The proposed method derives the intensity based variations that is large and small scale, from the source images. In this approach, guided filtering is employed for this extraction. Gaussian and Laplacian pyramidal approach is then used to fuse the different layers obtained. Experimental results demonstrate that the proposed method can obtain better performance for fusion of
all sets of images. The results clearly indicate the feasibility of the proposed approach.
It Works well on images while you want to edit an image or to repair old images. it also has great results on occluded images and good to use on censorship purposes. Appropriate reconstruction is one of its features.
one of the main and effective purposes is to complete images which have been destroyed during a time on SSDs or during transferring data in a transmission line or during transferring data between two devices such as laptop or Cellphones
Hope you all enjoy and make it as a reference
A CONCERT EVALUATION OF EXEMPLAR BASED IMAGE INPAINTING ALGORITHMS FOR NATURA...cscpconf
Image inpainting derives from restoration of art works, and has been applied to repair ancient
art works. Inpainting is a technique of restoring a partially damaged or occluded image in an
undetectable way. It fills the damaged part of an image by employing information of the
undamaged part according to some rules to make it look “reasonable” to human eyes. Digital
image inpainting is relatively new area of research, but numerous and different approaches to
tackle the inpainting problem have been proposed since the concept was first introduced. This
paper analyzes and compares the recent exemplar based inpainting algorithms by Minqin Wang
and Hao Guo et al. A number of examples on real images are demonstrated to evaluate the
results of algorithms using Peak Signal to Noise Ratio (PSNR)
Disparity Estimation by a Real Time Approximation AlgorithmCSCJournals
This paper presents an approximation real time algorithm for estimating the disparity of the stereo
images. The approximation is achieved by shrinking the left and right of original images.
According to this method (i ) left and right images have been shrinked three times,(ii) the disparity
image is computed from the shrinked left and right images to reconstruct the disparity image and
extrapolate the disparity image to retrieve the original image size. The computational time of
proposed algorithm is less than the existing methods, approximately real time and requires less
memory space. This method is applied on the standard stereo images and the results show that it
can easily reduce the computational time of about 76.34 % with no appreciable degradation of
accuracy.
Interpolation Technique using Non Linear Partial Differential Equation with E...CSCJournals
With the large use of images for the communication, image zooming plays an important role.
Image zooming is the process of enlarging the image with some factor of magnification, where
the factor can be integer or non-integer. Applying zooming algorithm to an image generally results
in aliasing; edge blurring and other artifacts. The main focus of the work presented in this paper is
on the reduction of these artifacts. This paper focuses on reduction of these artifacts and
presents an image zooming algorithm using non-linear fourth order PDE method combined with
edge directed bi-cubic algorithm. The proposed method uses high resolution image obtained from
edge directed bi-cubic interpolation algorithm to construct the zoomed image. This technique
preserves edges and minimizes blurring and staircase effects in the zoomed image. In order to
evaluate image quality obtained after zooming, the objective assessment is performed.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Development of stereo matching algorithm based on sum of absolute RGB color d...IJECEIAES
This article presents local-based stereo matching algorithm which comprises a devel- opment of an algorithm using block matching and two edge preserving filters in the framework. Fundamentally, the matching process consists of several stages which will produce the disparity or depth map. The problem and most challenging work for matching process is to get an accurate corresponding point between two images. Hence, this article proposes an algorithm for stereo matching using improved Sum of Absolute RGB Differences (SAD), gradient matching and edge preserving filters. It is Bilateral Filter (BF) to surge up the accuracy. The SAD and gradient matching will be implemented at the first stage to get the preliminary corresponding result, then the BF works as an edge-preserving filter to remove the noise from the first stage. The second BF is used at the last stage to improve final disparity map and increase the object boundaries. The experimental analysis and validation are using the Middlebury standard benchmarking evaluation system. Based on the results, the proposed work is capable to increase the accuracy and to preserve the object edges. To make the proposed work more reliable with current available methods, the quantitative measurement has been made to compare with other existing methods and it shows the proposed work in this article perform much better.
Stereo matching algorithm using census transform and segment tree for depth e...TELKOMNIKA JOURNAL
This article proposes an algorithm for stereo matching corresponding process that will be used in many applications such as augmented reality, autonomous vehicle navigation and surface reconstruction. Basically, the proposed framework in this article is developed through a series of functions. The final result from this framework is disparity map which this map has the information of depth estimation. Fundamentally, the framework input is the stereo image which represents left and right images respectively. The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. Based on the experimental results from the standard benchmarking evaluation system from the Middlebury, the disparity map results produce an average low noise error at 9.68% for nonocc error and 18.9% for all error attributes. On average, it performs far better and very competitive with other available methods from the benchmark system.
Matching algorithm performance analysis for autocalibration method of stereo ...TELKOMNIKA JOURNAL
Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods.
A new function of stereo matching algorithm based on hybrid convolutional neu...IJEECSIAES
This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. The main purpose of the stereo matching algorithm is to produce a disparity map. This map is essential for many applications, including three-dimensional (3D) reconstruction. The raw disparity map computed by a convolutional neural network (CNN) is still prone to errors in the low texture region. The algorithm is set to improve the matching cost computation stage with hybrid CNN-based combined with truncated directional intensity computation. The difference in truncated directional intensity value is employed to decrease radiometric errors. The proposed method’s raw matching cost went through the cost aggregation step using the bilateral filter (BF) to improve accuracy. The winner-take-all (WTA) optimization uses the aggregated cost volume to produce an initial disparity map. Finally, a series of refinement processes enhance the initial disparity map for a more accurate final disparity map. This paper verified the performance of the algorithm using the Middlebury online stereo benchmarking system. The proposed algorithm achieves the objective of generating a more accurate and smooth disparity map with different depths at low texture regions through better matching cost quality.
Comparison of Segmentation Algorithms and Estimation of Optimal Segmentation ...Pinaki Ranjan Sarkar
Recent advancement in sensor technology allows very high spatial resolution along with multiple spectral bands. There are many studies, which highlight that Object Based Image Analysis(OBIA) is more accurate than pixel-based classification for high resolution(< 2m) imagery. Image segmentation is a crucial step for OBIA and it is a very formidable task to estimate optimal parameters for segmentation as it does not have any unique solution. In this paper, we have studied different segmentation algorithms (both mono-scale and multi-scale) for different terrain categories and showed how the segmented output depends on upon various parameters. Later, we have introduced a novel method to estimate optimal segmentation parameters. The main objectives of this study are to highlight the effectiveness of presently available segmentation techniques on very high-resolution satellite data and to automate segmentation process. Pre-estimation of segmentation parameter is more practical and efficient in OBIA. Assessment of segmentation algorithms and estimation of segmentation parameters are examined based on the very high-resolution multi-spectral WorldView-3(0.3m, PAN sharpened) data.
An evaluation of two popular segmentation algorithms, the mean shift-based segmentation algorithm and a graph-based segmentation scheme. We also consider a hybrid method which combines the other two methods.
Abstract: Many applications such as robot navigation, defense, medical and remote sensing performvarious processing tasks, which can be performed more easily when all objects in different images of the same scene are combined into a single fused image. In this paper, we propose a fast and effective method for image fusion. The proposed method derives the intensity based variations that is large and small scale, from the source images. In this approach, guided filtering is employed for this extraction. Gaussian and Laplacian pyramidal approach is then used to fuse the different layers obtained. Experimental results demonstrate that the proposed method can obtain better performance for fusion of
all sets of images. The results clearly indicate the feasibility of the proposed approach.
It Works well on images while you want to edit an image or to repair old images. it also has great results on occluded images and good to use on censorship purposes. Appropriate reconstruction is one of its features.
one of the main and effective purposes is to complete images which have been destroyed during a time on SSDs or during transferring data in a transmission line or during transferring data between two devices such as laptop or Cellphones
Hope you all enjoy and make it as a reference
A CONCERT EVALUATION OF EXEMPLAR BASED IMAGE INPAINTING ALGORITHMS FOR NATURA...cscpconf
Image inpainting derives from restoration of art works, and has been applied to repair ancient
art works. Inpainting is a technique of restoring a partially damaged or occluded image in an
undetectable way. It fills the damaged part of an image by employing information of the
undamaged part according to some rules to make it look “reasonable” to human eyes. Digital
image inpainting is relatively new area of research, but numerous and different approaches to
tackle the inpainting problem have been proposed since the concept was first introduced. This
paper analyzes and compares the recent exemplar based inpainting algorithms by Minqin Wang
and Hao Guo et al. A number of examples on real images are demonstrated to evaluate the
results of algorithms using Peak Signal to Noise Ratio (PSNR)
Disparity Estimation by a Real Time Approximation AlgorithmCSCJournals
This paper presents an approximation real time algorithm for estimating the disparity of the stereo
images. The approximation is achieved by shrinking the left and right of original images.
According to this method (i ) left and right images have been shrinked three times,(ii) the disparity
image is computed from the shrinked left and right images to reconstruct the disparity image and
extrapolate the disparity image to retrieve the original image size. The computational time of
proposed algorithm is less than the existing methods, approximately real time and requires less
memory space. This method is applied on the standard stereo images and the results show that it
can easily reduce the computational time of about 76.34 % with no appreciable degradation of
accuracy.
Interpolation Technique using Non Linear Partial Differential Equation with E...CSCJournals
With the large use of images for the communication, image zooming plays an important role.
Image zooming is the process of enlarging the image with some factor of magnification, where
the factor can be integer or non-integer. Applying zooming algorithm to an image generally results
in aliasing; edge blurring and other artifacts. The main focus of the work presented in this paper is
on the reduction of these artifacts. This paper focuses on reduction of these artifacts and
presents an image zooming algorithm using non-linear fourth order PDE method combined with
edge directed bi-cubic algorithm. The proposed method uses high resolution image obtained from
edge directed bi-cubic interpolation algorithm to construct the zoomed image. This technique
preserves edges and minimizes blurring and staircase effects in the zoomed image. In order to
evaluate image quality obtained after zooming, the objective assessment is performed.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Development of stereo matching algorithm based on sum of absolute RGB color d...IJECEIAES
This article presents local-based stereo matching algorithm which comprises a devel- opment of an algorithm using block matching and two edge preserving filters in the framework. Fundamentally, the matching process consists of several stages which will produce the disparity or depth map. The problem and most challenging work for matching process is to get an accurate corresponding point between two images. Hence, this article proposes an algorithm for stereo matching using improved Sum of Absolute RGB Differences (SAD), gradient matching and edge preserving filters. It is Bilateral Filter (BF) to surge up the accuracy. The SAD and gradient matching will be implemented at the first stage to get the preliminary corresponding result, then the BF works as an edge-preserving filter to remove the noise from the first stage. The second BF is used at the last stage to improve final disparity map and increase the object boundaries. The experimental analysis and validation are using the Middlebury standard benchmarking evaluation system. Based on the results, the proposed work is capable to increase the accuracy and to preserve the object edges. To make the proposed work more reliable with current available methods, the quantitative measurement has been made to compare with other existing methods and it shows the proposed work in this article perform much better.
Stereo matching algorithm using census transform and segment tree for depth e...TELKOMNIKA JOURNAL
This article proposes an algorithm for stereo matching corresponding process that will be used in many applications such as augmented reality, autonomous vehicle navigation and surface reconstruction. Basically, the proposed framework in this article is developed through a series of functions. The final result from this framework is disparity map which this map has the information of depth estimation. Fundamentally, the framework input is the stereo image which represents left and right images respectively. The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. Based on the experimental results from the standard benchmarking evaluation system from the Middlebury, the disparity map results produce an average low noise error at 9.68% for nonocc error and 18.9% for all error attributes. On average, it performs far better and very competitive with other available methods from the benchmark system.
Matching algorithm performance analysis for autocalibration method of stereo ...TELKOMNIKA JOURNAL
Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods.
A new function of stereo matching algorithm based on hybrid convolutional neu...IJEECSIAES
This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. The main purpose of the stereo matching algorithm is to produce a disparity map. This map is essential for many applications, including three-dimensional (3D) reconstruction. The raw disparity map computed by a convolutional neural network (CNN) is still prone to errors in the low texture region. The algorithm is set to improve the matching cost computation stage with hybrid CNN-based combined with truncated directional intensity computation. The difference in truncated directional intensity value is employed to decrease radiometric errors. The proposed method’s raw matching cost went through the cost aggregation step using the bilateral filter (BF) to improve accuracy. The winner-take-all (WTA) optimization uses the aggregated cost volume to produce an initial disparity map. Finally, a series of refinement processes enhance the initial disparity map for a more accurate final disparity map. This paper verified the performance of the algorithm using the Middlebury online stereo benchmarking system. The proposed algorithm achieves the objective of generating a more accurate and smooth disparity map with different depths at low texture regions through better matching cost quality.
A new function of stereo matching algorithm based on hybrid convolutional neu...nooriasukmaningtyas
This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. The main purpose of the stereo matching algorithm is to produce a disparity map. This map is essential for many applications, including three-dimensional (3D) reconstruction. The raw disparity map computed by a convolutional neural network (CNN) is still prone to errors in the low texture region. The algorithm is set to improve the matching cost computation stage with hybrid CNN-based combined with truncated directional intensity computation. The difference in truncated directional intensity value is employed to decrease radiometric errors. The proposed method’s raw matching cost went through the cost aggregation step using the bilateral filter (BF) to improve accuracy. The winner-take-all (WTA) optimization uses the aggregated cost volume to produce an initial disparity map. Finally, a series of refinement processes enhance the initial disparity map for a more accurate final disparity map. This paper verified the performance of the algorithm using the Middlebury online stereo benchmarking system. The proposed algorithm achieves the objective of generating a more accurate and smooth disparity map with different depths at low texture regions through better matching cost quality.
Towards better performance: phase congruency based face recognitionTELKOMNIKA JOURNAL
Phase congruency is an edge detector and measurement of the significant feature in the image. It is a robust method against contrast and illumination variation. In this paper, two novel techniques are introduced for developing alow-cost human identification system based on face recognition. Firstly, the valuable phase congruency features, the gradient-edges and their associate dangles are utilized separately for classifying 130 subjects taken from three face databases with the motivation of eliminating the feature extraction phase. By doing this, the complexity can be significantly reduced. Secondly, the training process is modified when a new technique, called averaging-vectors is developed to accelerate the training process and minimizes the matching time to the lowest value. However, for more comparison and accurate evaluation,three competitive classifiers: Euclidean distance (ED),cosine distance (CD), and Manhattan distance (MD) are considered in this work. The system performance is very competitive and acceptable, where the experimental results show promising recognition rates with a reasonable matching time.
Stereo vision-based obstacle avoidance module on 3D point cloud dataTELKOMNIKA JOURNAL
This paper deals in building a 3D vision-based obstacle avoidance and navigation. In order for an autonomous system to work in real life condition, a capability of gaining surrounding environment data, interpret the data and take appropriate action is needed. One of the required capability in this matter for an autonomous system is a capability to navigate cluttered, unorganized environment and avoiding collision with any present obstacle, defined as any data with vertical orientation and able to take decision when environment update exist. Proposed in this work are two-step strategy of extracting the obstacle position and orientation from point cloud data using plane based segmentation and the resultant segmentation are mapped based on obstacle point position relative to camera using occupancy grid map to acquire obstacle cluster position and recorded the occupancy grid map for future use and global navigation, obstacle position gained in grid map is used to plan the navigation path towards target goal without going through obstacle position and modify the navigation path to avoid collision when environment update is present or platform movement is not aligned with navigation path based on timed elastic band method.
Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region IJECEIAES
This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method.
A deep learning based stereo matching model for autonomous vehicleIAESIJAI
Autonomous vehicle is one the prominent area of research in computer
vision. In today’s AI world, the concept of autonomous vehicles has become
popular largely to avoid accidents due to negligence of driver. Perceiving the
depth of the surrounding region accurately is a challenging task in
autonomous vehicles. Sensors like light detection and ranging can be used
for depth estimation but these sensors are expensive. Hence stereo matching
is an alternate solution to estimate the depth. The main difficulties observed
in stereo matching is to minimize mismatches in the ill-posed regions, like
occluded, texture less and discontinuous regions. This paper presents an
efficient deep stereo matching technique for estimating disparity map from
stereo images in ill-posed regions. The images from Middlebury stereo data
set are used to assess the efficacy of the model proposed. The experimental
outcome dipicts that the proposed model generates reliable results in the
occluded, texture less and discontinuous regions as compared to the existing
techniques.
An Image Enhancement Approach to Achieve High Speed using Adaptive Modified B...TELKOMNIKA JOURNAL
For real time application scenarios of image processing, satellite imaginary has grown more interest by researches due to the informative nature of image. Satellite images are captured using high quality cameras. These images are captured from space using on-board cameras. Wrong ISO setting, camera vibrations or wrong sensory setting causes noise. The degraded image can cause less efficient results during visual perception which is a challenging issue for researchers. Another reason is that noise corrupts the image during acquisition, transmission, interference or dust particles on the scanner screen of image from satellite to the earth stations. If quality degraded images are used for further processing then it may result in wrong information extraction. In order to cater this issue, image filtering or denoising approach is required.
Since remote sensing images are captured from space using on-board camera which requires high speed operating device which can provide better reconstruction quality by utilizing lesser power consumption. Recently various approaches have been proposed for image filtering. Key challenges with these approaches are reconstruction quality, operating speed, image quality by preserving information at edges on image.
Proposed approach is named as modified bilateral filter. In this approach bilateral filter and kernel schemes are combined. In order to overcome the drawbacks, modified bilateral filtering by using FPGA to perform the parallelism process for denoising is implemented.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This article aims at a new algorithm for tracking moving objects in the long term. We have tried to overcome some potential difficulties, first by a comparative study of the measuring methods of the difference and the similarity between the template and the source image. In the second part, an improvement of the best method allows us to follow the target in a robust way. This method also allows us to effectively overcome the problems of geometric deformation, partial occlusion and recovery after the target leaves the field of vision. The originality of our algorithm is based on a new model, which does not depend on a probabilistic process and does not require a data based detection in advance. Experimental results on several difficult video sequences have proven performance advantages over many recent trackers. The developed algorithm can be employed in several applications such as video surveillance, active vision or industrial visual servoing.
The active safety systems used in automotive field are largely exploiting lane detection technique for warning the vehicle drivers to correct any unintended road departure and to reach fully autonomous vehicles. Due to its ability, to be programmed, to perform complex mathematical functions and its characterization of high speed processing, Field Programmable Gate Array (FPGA) could cope with the requirement of lane detection implementation and application. In the present work, lane detection is implemented using FPGA for day vision. This necessitates utilization of image processing techniques like filtering, edge detection and thresholding. The lane detection is performed by firstly capturing the image from a video camera and converted to gray scale. Then, a noise filtering process for gray image is performed using Gaussian and average filter. Methods from first and second order edge detection techniques have been selected for the purpose of lane edge detection. The effect of manually changing the threshold level on image enhancement has been examined. The results showed that raising threshold level would better enhance the image. The type of FPGA device used in the present work is Altera DE2. Firstly, the version DE2 Cyclone II start with (11xxxxxx-xxxx) together with Genx camera has been used. This camera supports both formats NTSC and PAL, while the above version of FPGA backups only NTSC format. The software of lane detection is designed and coded using Verilog language.
Similar to Stereo matching based on absolute differences for multiple objects detection (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
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Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
2. ISSN: 1693-6930
TELKOMNIKA Vol. 17, No. 1, February 2019: 261-267
262
each pixel on image. Last step is known as refinement stage or post-processing step to
decrease the outstanding invalid pixels or noise on the final disparity map.
Generally, there are two foremost methods in stereo matching algorithm which are
recognized as local and global methods [2]. The classification is held by the method on by what
method the disparity is calculated. To define the disparity map based on the energy
minimization method or function is used in global approach. The calculation is built on the
flatness position from closer pixels which uses the minimization of global energy function. One
of the well-known method in global method is the Markov Random Field (MRF) that measures
the energy function. Several established methods using the MRF were Belief Propagation
(BP) [3] and Graph Cut (GC) [8] which applied the energy minimization technique. The BP
technique employed the MRF by incessantly absolution pointers from present point to the
nearby points or neighbors. Else, the GC method uses the MRF approach by maximizing flow
rule and cut the smallest energy flow structure. Global methodologies obtain low precision on
images with radiometric problem and the framework require complex calculation to process high
resolution images [9].
Local approach processes using local structures or contents. This method works based
on a support region in predefined sizes. There are many published methods using local-based
approach or using window-based methods such as convolution neural network [10], multiple
window, fixed window and adaptive window. The benefit of a local approach is low calculation
on the computational requirement and acquires fast time execution. Local approaches use the
Winner-Takes-All (WTA) strategy in the disparity selection and optimization step. The WTA
utilizes a lowest raw data from aggregation step. Then, it will be normalized the raw data to the
minimum disparity value. Recently, numerous local approaches have been developed.
Hu et al. [11] proposed a complex method using simulated support window. This method
requires multiple estimations which increases the time execution. Inecke and Eggert [12]
imposed a modification of normalized cross correlation (NCC) function at earlier step that
decreases the accuracy of preliminary differences. Hence, their approach yields enormous
noise and invalid pixels on the objects edges. Frequently, local approaches produce high error
on the object edges because of inappropriate selection of the windows filter size. Therefore, the
challenge is to get an accurate window size for local method to increase the accuracy.
This article offers a novel stereo matching algorithm using pixel-based matching cost
computation. Then, the aggregation stage utilizes a guided filter (GF) [13] with fixed windows
size. The GF is capable to eliminate the noise and preserved the object edge. The propose
algorithm follows the structure of a local method. Therefore, the optimization is using the WTA
strategy. The final stage of the algorithm, a bilateral filter (BF) is employed. The BF is strong
against the illumination changes and efficient in removing the noise. This article is arranged as
follows. Section 2 describes the methodology or the planned algorithm framework. Then,
section 3 explains the experimental setup and the discussion of the disparity map results with
qualitative and quantitative measurement. The final part is the conclusion and the
acknowledgement.
2. Research Method
Figure 1 displays the framework of the proposed work. The first step uses pixel base
correspondence method known as absolute differences. Then, a guided filter (GF) will be used
at cost aggregation stage. After that, the WTA will be implemented at disparity optimization step
to select the minimum disparity value. The final stage is using a bilateral filter (BF) to remove
the remaining invalid disparity and increases the accuracy of final disparity map.
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Figure 1. A flowchart of the proposed algorithm
2.1. Matching Cost Computation
This stage is the first step of the algorithm structure which estimates the matching
differences of the preliminary data between stereo images. Therefore, this phase is the most
important part in the algorithm structure. The method used at this step must be robust and is
capable to avoid from too many noise. Thus, the proposed work uses the absolute differences
(AD) function which treats each pixel individually and the properties of the pixel can fully have
utilized. The AD computes the horizontal direction along the grayscale values on each pixel of
stereo image. The benefit of the AD is that this function is fast and capable to preserve the
properties of each pixel. The AD function is represented by (1) follows:
AD(𝑥, 𝑦, 𝑑) = 𝐼𝑙(𝑥, 𝑦) − 𝐼𝑟(𝑥, 𝑦, 𝑑) (1)
where I represents the pixel intensity at the coordinates (x,y) and d represents the disparity
value of left to right image differences.
2.2. Cost Aggregation
The cost aggregation is the second step of the local-based algorithm structure. This
step decreases noise from the first stage to filter the preliminary result with more consistent
matching differences before the next stage of optimization and disparity selection. This article
recommends the usage of edge-preserving filter where this filter is capable to remove the noise
and preserved the object’s edges detection. Hence, this work uses the guided filter (GF) which
was developed by He et al. [13]. The filter kernel is shown by the (2):
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𝐺𝐹(𝑝,𝑞)(𝐼) =
1
𝑤2
∑ (1 +
(𝐼 𝑝−𝜇 𝑐)(𝐼 𝑞−𝜇 𝑐)
𝜎 𝑐
2+𝜀
)(𝑝,𝑞)∈𝑤 𝑐
(2)
where {p,q,w,c,ε,σ,µ,I} denoted by { coordinates of (x,y), neighboring coordinates, window
support size, center pixel of w, constant parameter, variance value, mean value, reference
image (left input image)}. The GF is utilized in this work in line for fast execution of time
processing which the calculation is only depend on the image pixels. The GF is able to increase
the accuracy at the object edges. The final equation of this stage is given by (3):
𝐶𝐴(𝑥, 𝑦, 𝑑) = 𝐴𝐷(𝑥, 𝑦, 𝑑)𝐺𝐹(𝑝,𝑞)(𝐼) (3)
where 𝐴𝐷(𝑥, 𝑦, 𝑑) is the input of the first stage and 𝐺𝐹(𝑝,𝑞)(𝐼) represents the kernel of the GF
with left image as a reference image in this article.
2.3. Disparity Optimization
The third step of the structure is the disparity optimization and selection which reduces
the data assortment on the disparity positions and represented it with disparity value.
Commonly, the local based stereo matching algorithm is consuming the Winner-Takes-All
(WTA) strategy [9]. The WTA usages the minimum value of 𝐶𝐴(𝑥, 𝑦, 𝑑) and embodied the same
location with the disparity value. The function of the WTA stage is given by (4):
𝑑(𝑥, 𝑦) = arg min 𝑑∈𝐷 𝐶𝐴(𝑥, 𝑦, 𝑑) (4)
where D denotes the range of disparity on an image, d(x,y) is the selected disparity value at the
location of (x,y) and 𝐶𝐴(𝑥, 𝑦, 𝑑) is the value of the second stage.
2.4. Post-processing
The post-processing step is the last stage of the algorithm framework. This stage is also
known as filtering stage or disparity refinement stage which decreases the invalid disparity
values and the outlier noise on the final results [14]. Fundamentally, the used of second filtering
process at this step is to surge the effectiveness and accurateness of the final disparity map.
The suggested work in this article is using the bilateral filter (BF) which works for the second
filtering process. The final disparity result is given by the (5):
𝐵𝐹(𝑝,𝑞) = ∑ exp (−
|𝑝−𝑞|2
𝜎𝑠
2 ) 𝑒𝑥𝑝 (−
|𝐼 𝑝−𝐼 𝑞|2
𝜎 𝑐
2 )𝑞∈𝑤 𝐵
(5)
where the (p,q) represent the pixel of interest and neighbor pixel coordinates, wb denotes the BF
window size, |𝐼 𝑝 − 𝐼𝑞|2
and |𝑝 − 𝑞| are the intensity differences and spatial distance
respectively, 𝜎𝑠
2
and 𝜎𝑐
2
are the spatial distance and color similarity parameters.
3. Results and Analysis
This section provides the experimental setup and results of the proposed work in this
article. All of the experiment were executed using a personal computer with the features of
CPU i7-5500 and 8G RAM. The standard benchmarking dataset have been used in this article
from the Middlebury Stereo evaluation benchmark [15]. This article also uses the KITTI
benchmarking dataset. The KITTI dataset was developed by Menze and Geiger [16] which
consists of 200 training images. This dataset was recorded from real environment of
autonomous vehicle navigation using a stereo vision system. Hence, it comprises very
challenging and complex images for the evaluation of stereo matching algorithm. The
performance is measured based on the all and nonocc error attributes of bad pixel percentages.
The all error is the error of invalid disparity values on all pixels of the disparity map image. The
nonocc error is the error of invalid disparity values on the non-occluded regions [17-18]. The
difference between these two errors is all error calculates all pixel, but the nonocc only counted
the pixels in the certain regions (i.e., nonoccluded regions). The quantitative results in this
article are evaluated based on the development kit provided by the KITTI. Some other
methods [19-22] used different methodology of evaluation to get the performance results.
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Figure 2 shows the results of objects detection using the Middlebury images. The
objects are well-detected and reconstructed on the maps such as a mug in the Adirondack, the
brushes in ArtL, a tree in Jadeplant, a motorcycle in Motorcycle, the personal computer in
Vintage, piano and a chair in Piano, a recycle box in Recycle and a chair in the Shelves image.
The complex images such as the pipes structures in the Pipe image are also well-reconstructed.
The chairs are well discovered on the Playroom and Playtable images. It shows that the
proposed framework in this article is capable to detect and reconstruct the detected objects.
Figure 2. The results from the Middlebury Stereo Evaluation dataset
Table 1 displays the quantitative results of the proposed framework with some
published methods. As for comparison before and after the proposed work, the TestG is the
algorithm without the proposed framework which uses common algorithm with the first stage
using interpolation matching technique. Second stage is using box filter with WTA strategy at
optimization step. The last stage uses median filter with fixed windows size. The proposed
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algorithm is ranked at top of the table with 12.11% and 14.01% of nonocc and all errors
respectively. If compared with the TestG algorithm, the proposed work reduces the nonocc and
all errors with 18.20% and 20.47% respectively. The second algorithm produced by 3D, and
followed by Hu, NCC, GC and BP.
Table 1. The Results of the KITTI Training Dataset
Algorithm Nonocc error (%) All error (%)
Proposed work 12.11 14.01
SSW [17] 12.75 14.22
Hu [11] 13.55 16.65
NCC [12] 14.11 15.79
GC [8] 14.34 15.98
BP [3] 15.67 17.84
TM [18] 19.65 21.21
TestG 30.31 34.48
Figure 3 displays the sample results of objects detection using the KITTI dataset. The
first image shows a car and the trees which the proposed work is capable to detect these
objects on the disparity map. The contour of the color mapping on the detected objects are
well-recognized on the disparity map result. The second until the fifth images show the cars are
also well-reconstructed on the disparity map. The moving objects such as a lorry and a car in
the last image are well-detected and reconstructed on the final result. In average, the different
contour of disparity levels based on the different color scheme are precisely displayed on each
result in this figure. It shows that the proposed algorithm is capable to work with real images as
shown by the results using the KITTI dataset.
Figure 3. Sample results of objects detection from the KITTI dataset
4. Conclusion
A new framework of stereo matching algorithm was presented in this article. This
algorithm was capable to detect any object based on the input from the stereo vision sensor.
This algorithm is also capable to detect and robust against the moving objects as shown by the
results in the KITTI dataset. Additionally, the proposed framework is able to increase the
accuracy compared with TestG as tabulated in Table 1. The framework is also competitive with
some established methods as tabulated in the same table.
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Acknowledgement
This work is supported by a grant from the Universiti Teknikal Malaysia Melaka with the
reference number PJP/2018/FTK(13C)/S01632.
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