ABSTRACT Plant disease classification using image processing techniques is a prominent and challenging area of research. We have developed a novel classification technique to classify, especially spot and blight diseased leaf images of four different plant species. In this technique, we have dealt with the infection patterns manifested on leaves. The infection patterns seem to correlate with diseases

ABSTRACT Infrared thermography lends countless applications in biology and veterinary science. The popularity of the use of infrared imaging in the detection and mitigation of animal diseases has increased recently because of its non-invasiveness, ease of automation and keen sensitivity. The current review addresses the applicability of thermographic imaging for the diagnosis of common swine diseases

ABSTRACT Plant disease classification using image processing techniques is a prominent and challenging area of research. We have developed a novel classification technique to classify, especially spot and blight diseased leaf images of four different plant species. In this technique, we have dealt with the infection patterns manifested on leaves. The infection patterns seem to correlate with diseases

ABSTRACT The Optical Character Reader (OCR) process means the transition from scanned manual or written images to a machine-determined document. The American Standard Code for Information Interchange (ASCII) in cognitive processing uses OCR. The challenge is two primary folds: word segmentation by letters and character recognition. Implement a new approach to include the two functions by Scale-Invariant

A novel SPECT model with an elliptical orbit and multiple detectors is proposed for detecting the metabolism of the human heart. Under the structure of the proposed model, the distance between the detector and the patient becomes smaller, which can effectively improve the SNR. The slit-slat collimator is used to collimate the emitted photons. Modified iterative reconstruction algorithm is proposed

ABSTRACT A novel SPECT model with an elliptical orbit and multiple detectors is proposed for detecting the metabolism of the human heart. Under the structure of the proposed model, the distance between the detector and the patient becomes smaller, which can effectively improve the SNR. The slit-slat collimator is used to collimate the emitted photons. Modified iterative reconstruction algorithm is

Image super-resolution (SR) techniques aim to estimate high-resolution (HR) image from low-resolution (LR) image. Existing SR method has slow convergence and recovery of high-frequency details are inaccurate. To overcome these issues, two algorithms have been proposed for image SR based on non-local means improved iterative back projection (NLM-IIBP), deep convolutional neural network improved iterative

Motion estimation (ME) being a fundamental process of crowd behavior analysis experienced real challenges at high densities due to visual ambiguities and occlusion problems etc. Various surveys reported in the past years summarize conventional ME methods for crowd behaviors at low/medium densities. In this paper, we focus on state-of-the-art fluid dynamics (FD) ME methods developed over the last one

Sign language is a medium of communication for people with hearing disabilities. Static and dynamic gestures are identified in a video-based sign language recognition and translated them into humanly understandable phrases to achieve the communication objective. However, videos contain redundant Key-frames which require additional processing. Number of such Key-frames can be reduced. The selection

An architecture for automatic lung tissue classification method based on the Deep Learning techniques is designed in this paper. Recent works on Deep Learning techniques achieved impressive results in the field of medical image classification. So, we designed a Convolution Neural Network (CNN) for the classification of five categories of Interstitial Lung Diseases (ILD) patterns in High-Resolution

The existing location anonymity algorithms do not consider the distribution of user density in the region. The area of anonymous domain is not the most appropriate and the query workload is redundant. To solve this problem, this paper proposes optimal anonymous location privacy protection algorithm based on grid user density. Taking the user density of the regional grid as the core and using reasonable

Image recoloring using wavelet transform, in-painting and dichromatic reflection model is proposed. Detailed wavelet bands are passed through a sharpening filter whereas the approximation band is passed through dichromatic reflection model to extract body and specular coefficients. In-painting and white illumination minimization using erosion and Gaussian blur further enhance the image quality. The

ABSTRACT In this manuscript, a technique for the fast retrieval and dose saving single-shot imaging of X-ray scattering information based on angular signal radiography and the staggered grating is simulated. A staggered grating is used to encode two sample images into a single exposure. Results show that single-shot X-ray scattering imaging, being low dose, can be used for biomedical applications where

In recent times, the applications of multimedia are rising in a greedy mode and hence the amount of video transactions is also increasing exponentially. This has shouted great demands on effective models on video encoding and also for reducing the transmission channel congestion. This research work introduces a managing technique termed weighted encoding for High-Efficiency Video Coding (HEVC). HEVC

Watermarking provides an efficient mechanism for copyright protection of digital media by embedding information in the object to identify the owner. This paper proposed a watermarking technique that can successfully embed a grey-scale image in a 3D mesh object. In our proposed technique, each three vertices of the 3D object can hide one pixel from the secret image. The experimental results showed that

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features

Face Recognition is the process of identifying and verifying the faces. Face recognition has vast importance in the field of Security, Healthcare, Banking, Criminal Identification, Payment, and Advertising. In this paper, we have reviewed various techniques and challenges for the face recognition. Illumination, pose variation, facial expressions, occlusions, aging, etc. are the key challenges to the

Surface Fourier transform profilometry (FTP) is a technique used for reconstructing three-dimensional (3-D) surface topography using light. It has been widely used in machine vision for biomedical and biometric automations, providing solutions beyond conventional 2-D imaging. This paper proposes an implementation of the handheld pocket-size FTP for 3-D surface profile imaging using a projector-enabled

A single pixel in time of flight cameras receives multiple reflected light from different scene points, resulting in erroneous depth information. In this paper, based on the proposed sparse decomposition, a coarse and fine sparse decomposition based on compressed sensing is applied to multipath separation. The applied method uses a linear combination of multiple frequency signals to modulate the source

Image segmentation [Gonzalez RG, Woods RE. Third edition digital image processing. South Asia: Pearson; 2014, Sridhar S. Digital image processing. India: Oxford; 2011] is a very important step in applications of the image processing field. Segmentation will divide the image into different parts and extract a required area known as Region of Interest (ROI). ROI varies with applications. For the effective

Objective: To observe the prognosis of RRDCD after vitrectomy using OCTA. Methods: We gathered information of three groups including RRDCD group, RRD group and normal control group respectively whose superficial and deep retinal VD, FAZ, FT and SFCT were detected via OCTA. Afterwards, chi-square test, independent sample T-test and least significant difference (LSD) method were used as the statistical

The objective of our venture is to actualize a lane detection framework considering expanding the usability of driver assistance system functions, attempting to overcome the problems of the generalized method. It is tuned to detect mountainous roads on the Indian hilly terrain. The proposed technique acquires a video sequence as input and performs operation on each frame to extract the candidate lane

Leukemia is the abnormal and uncontrolled development of the white blood cells, known as leukocytes, in the blood. The manual methods used for counting the blast cells have some demerits, and so automatic method must be employed. This paper proposes the Salp Swarm integrated Dolphin Echolocation-based Support Vector Neural Network (SSDE-SVNN) classifier to detect leukemia in its early stages. The pre-processed

Tumours, one of the pathologies of the brain, are diverse in shape and appearance and overlap with the normal brain tissues making accurate automatic segmentation a challenge. This work proposes a semi- automatic, unsupervised method for brain tumour segmentation, using magnetic resonance images in a simple Bayesian framework. Pixel is classified as a tumour class by taking into account the knowledge

Percutaneous ethanol injection of hepatocellular carcinoma is indicated for the treatment of small tumours superimposed on liver cirrhosis. It involves destroying the cancer cells of the liver by injecting ethanol using a needle placed in the centre of the tumour under ultrasound or computed tomography scanner. A precise pre-operative planning of such intervention is a major challenge for a successful

Breast cancer is a significant health concern prevailing in both developing and developed countries. However, early detection of the disease receives significant attention to the medical community due to the enhanced chances of patient survival. Widely used screening modalities for the breast cancer are mammography, magnetic resonance imaging and ultrasound imaging. However these techniques have limited

Background subtraction is generally used to detect moving objects, because it has low complexity, and it is easy to implement. However, the detection error increases when the background is changing. Therefore, adaptive background subtraction is applied to overcome this problem, and it continuously requires updating the background with a fixed learning rate. The learning rate should be tuned for a consistently

Varicose ulcers occur due to improper functioning of venous valves in legs. These ulcers are the severe external signs of vein-related problems, such as chronic pain, leg swelling and leg heaviness. The aim of the proposed methodology is to increase better diagnosis and treatment results by computer-assisted tissue classification (granulation, slough, necrotic and epithelial) of varicose ulcer using

Handwritten optical character recognition (OCR) is the renowned research area in several fields, like writers identification, bank cheques, and so on. Literature works presented the handwritten OCR for various languages. This paper proposes a hybrid neural network training algorithm for English handwritten OCR. Initially, the noise in the input image is removed using the median filter, and the image

Copy-move forgery is one of the most popular tampering artefacts in digital images. However, tampering effect in digital images makes the authentication of the processing as untrustworthy. In this paper, a combination of Fourier-Mellin and Zernike moments (FMZM) Transform is proposed which detects the copy-move region with high-speed and low-computational complexity. Here, initially an image is segmented

This paper presents a novel age function modelling technique on the basis of the fusion of local features obtained by local texture descriptors. Initially, image normalization is performed and a feature extraction process is carried out. The age estimation performances of new texture descriptors Local Phase Quantization, Weber Local Descriptor and the familiar texture descriptor Local Binary Patterns

Blue–green colour cast effect and low contrast are common problems suffered by deep underwater images. This paper introduces a new method which consists of two major steps: red channel correction based on green and blue channels (RCCGB), and simultaneous contrast stretching and mean pixel enhancement (SCSMPE). The RCCGB is designed to minimize the effect of blue–green illumination. This step considers

In this paper, a hybrid model is developed by integrating a non-linear regression model and optimization-driven deep learner for video super resolution. Initially, the low-resolution frames are subjected to framing, and each frame is provided to both Fractional-Group Search Optimizer-based Deep Belief Network (FrGSO-DBN) classifier and the nonlinear regression model. Then, the output frames of both

Deep metric learning has become a general method for person re-identification (ReID) recently. Existing methods train ReID model with various loss functions to learn feature representation and identify pedestrian. However, the interaction between person features and classification vectors in the training process is rarely concerned. Distribution of pedestrian features will greatly affect convergence

The representation of colour in digital images is based on the response of camera used to capture the image, and how light interacts with the sensor in the respective red, green and blue channels. In Ultraviolet and Infrared, we have no reference for how they should look as we cannot directly observe them. A novel approach for the analysis of how a commercial SLR camera captures colour as a function

This paper presents an effective lip pixel detection method based on blocks and deep neural networks. Since only-rough localization of a pair of lips is a trivial task, we use a rectangle that loosely bounds two lips as an input region of interest for lip detection. For each pixel in the rectangle region we generate a block whose center is at the pixel, and the pixel is classified into either a lip

The goal of motion segmentation is to segregate a visual scene into independently moving objects. It is an indispensable pre-processing step for various tasks in computer vision and has evolved as an active and flourishing research area in the last few decades. In the sequences captured using a monocular camera, motion segmentation is typically performed by analyzing apparent motion of pixels in the

Owing to local linear model, guided image filter may contain from ringing artefacts. A modified guided image filter based on data mining techniques and decomposition is proposed in this paper. Image is split into patches, passing through the guided filter, clustered into number of clusters and transformed into compact domain using principal component analysis. Edges are preserved and halo artefacts

In this work, we propose a new adaptive chaotic steganographic method based on the Discrete Cosine Transform (DCT) and a reversible mapping function. The mapping function is used to map the secret bits into their corresponding symbols. This mapping technique has to preserve the same dynamics, properties and distribution of the original DCT coefficients. The novelty of our approach is based on the adaptive

In this research work, a 40-km2 SPOT-5 High-Resolution Imagery (HRI) of the Warsak locality in district Peshawar, Pakistan, was utilized to approximate the quantity of cultivated land lost to urbanization, due to the construction of new homes and buildings. The imagery from a period of 2005 to 2015 for wheat crop was taken, specifically during the months of March and June when the crop is rich green

In order to improve speckle noise denoising of block matching and 3D filtering (BM3D) method, an image frequency-domain multi-layer fusion enhancement method (MLFE-BM3D) based on nonsubsampled contourlet transform (NSCT) has been proposed. The method designs an NSCT hard threshold denoising enhancement to preprocess the image, then uses fusion enhancement in NSCT domain to fuse the preliminary estimation

The dual stego images based on data hiding has become popular in recent days. Since the embedding rate in dual stego images is very high. This paper proposes a new data encoding method based on maximum to the minimum histogram in reversible data hiding. This method estimates the encoded intensity from the message intensity and embeds the encoded intensity in the cover image. The stego image quality

The impact of fraud on the world economy is significant. As fraud has evolved it has become more organized and increasingly cyber-enabled and committed across borders of law enforcement jurisdictions. The technological demands facing fraud investigators are increasing. Yet, little attention has been given to how forensic photography can help tackle emerging crime types, like fraud. This study reviews

In order to retrieve large scale damaged image with rich geometry structure and texture information, the novel image inpainting algorithm based on the neighbourhood reference priority can not only maintain image character but also improve image inpainting speed has been proposed in the paper. The problems of an image inpainting process can be translated into the best sample searching process. First

Images captured under low-illumination environments often impose difficulties in revealing objects of interest. An effective approach, Optimum Shift-and-Weighted Brightness Mapping, is here proposed that can optimally enhance the image for higher brightness, information content, and colour vividness. Specifically, the input-output brightness mapping is determined by a shifted spline curve and a larger

In recent years, a spatio-temporal context (STC) algorithm has attracted the attention of scholars, due to the algorithm makes full use of the information of the target background. Although the STC algorithm achieve tracking at the real-time, but there is still a need to improve the tracking capability when the target is occluded or the size of the target changes. In this paper, we presented an adaptive

To preserve archive films of which the base material is composed of cellulose acetate, we carried out screening tests on various reagents. We selected sodium carbonate and sodium polyacrylate as an acetic acid gas removing agent and a dehumidification agent, respectively. The performance of sodium carbonate per unit mass in the removal of acetic acid gas was superior to those of commercial products

Slope and slant correction of offline handwritten word images are two of the major pre-processing steps in document image processing, because these reduce the variations in writing, thereby make further processing of the same much easier. This paper presents novel slope and slant correction methods that are applied in three different script handwritten words namely Devanagari, Bangla and Roman. The

This paper presents the security analysis of a recently proposed data hiding scheme by Kanan and Nazeri [A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm. Expert Syst Appl. 2014;41(14):6123–6130]. Security of the scheme depends upon a secret key\chromosome constructed using a genetic algorithm. The key specifies offsets and

Digital image processing is a mechanism for analysing and modifying the image in order to improve the quality and also to manage the unwanted involvement of noises. In image processing, noise is characterized as an unwanted disturbance which occurs while capturing the actual image thus affecting the quality of the image. Hence, noise formation is considered as a perilous issue and the reduction of

Image compression has become an inevitable tool along with the advancing medical data acquisition and telemedicine systems. The run-length encoding (RLE), one of the most effective and practical lossless compression techniques, is widely used in two-dimensional space with common scanning forms such as zigzag and linear. In this study, an algorithm which takes advantage of the potential simplicity of

This paper presents the results of the influence of simultaneous contrast effect on the shift in viewer perception of lightness, depending on the display on which the effect is being evaluated in relation to reproduction. By using simultaneous binocular harmonization technique 55 participants had a task of harmonizing the test primary stimuli presented on two different displays with the referential

The major problem in underwater image processing involves light attenuation. In order to overcome such light incorporation and dispersion issues, this paper proposes a new underwater image enhancement model that includes certain phases like contrast correction and colour correction. Here, two processes are worked out in contrast correction namely (i) global contrast correction and (ii) local contrast

In this paper, a unique approach is proposed to determine eye strain in children caused due to the prolonged exposure to LCD and PDP screens. Blink rate and area of eye sclera are the two efficient metrics relied upon to determine eye strain. Initially, blink rate is computed by monitoring state transitions from open to closed eyes. To segment the sclera region of the eye Otsu’s thresholding and colour

Aim to that Neutrosophic C-mean clustering segmentation does not consider the membership distribution of every sample point to different classes. Herein, an image-segmentation algorithm based on wavelet and data-driven neutrosophic fuzzy clustering is proposed. When the maximum membership value of a sample point is far greater than other membership values, the centre of the class with the maximum membership

Currently, high-resolution SAR data is available from different satellites. These datasets have been proved to be a strong source to monitor land subsidence. This paper aims to use high-resolution Persistent Scatterers Interferometry (PSI) to estimate the urban subsidence in Delhi NCR. TerraSAR-X images in 68 numbers spread over a period of 26 months during September 2011 – September 2013 have been

In this paper, a complete and fully automatic MRI brain tumour detection and segmentation methodology is presented as an efficient clinical-aided tool using Gaussian mixture model, Fuzzy C-Means, active contour, wavelet transform and entropy segmentation methods. The proposed algorithm is based on two main parts: the skull stripping and tumour auto-detection and segmentation. The first part was evaluated

This work proposes a simple yet efficient way to estimate pedestrians flow direction based on videos from still cameras. It does that by localizing the extremities of head and feet of silhouettes and fitting them to lines. As the previous in three-dimensional space of these lines are parallel, their intersection point is the vanishing point. Using the computed vanishing point and two internal camera

A novel approach for object categorization suitable for video surveillance is proposed. We describe shapes only using radius and arclength of their curvatures, which allow differentiating between objects that appear in the monitored area. We conducted experiments on classes such as pedestrians, cars, cyclists, and animals (horse, cow, dog, and cat). Our approach achieves a reasonable accuracy ( 95

The standardization of images derived from different medical modalities should be ensured when image fusion brings essential information and hybrid scanners are not available. The aim of this study was to show that precise image fusion standardization can be obtained using special and unique multimodal heart phantom (MHP) which is compatible with all applied diagnostic methods. MHP was designed and