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LBP and Weber law descriptor feature based CRF model for detection of man-made structures

Suchismita Behera, P. K. Nanda

2015 International Conference on Man and Machine Interfacing (MAMI) > 1 - 6

2015 International Conference on Man and Machine Interfacing (MAMI)

In this paper, we have proposed a combined Local Binary Pattern (LBP) and Weber Law Descriptor (WLD) feature based Conditional Random Field (CRF) model for detection of man made structures such as buildings in natural scenes. In natural scenes, the structure may have textural attributes or some portions of the object may be apparent as textures. The CRF model learning has been carried out in feature...

article

Face recognition based on curvelets and local binary pattern features via using local property preservation

Lijian Zhou, Wanquan Liu, Zhe-ming Lu, Tingyuan Nie, more

The Journal of Systems & Software > 2014 > 95 > Complete > 209-216

In this paper, we propose a new feature extraction approach for face recognition based on Curvelet transform and local binary pattern operator. The motivation of this approach is based on two observations. One is that Curvelet transform is a new anisotropic multi-resolution analysis tool, which can effectively represent image edge discontinuities; the other is that local binary pattern operator is...

article

Hybrid texture and gradient modeling for dynamic background subtraction identification systemin tobacco plant using 5G data service

M.T. Gowda Thirthe, J. Chandrika

Computer Assisted Methods in Engineering and Science > 2023 > Vol. 30, no. 1 > 41--54

Background: Detecting the plants as objects of interest in any vision-based input sequence is highly complex due to nonlinear background objects such as rocks, shadows,etc. Therefore, it is a difficult task and an emerging one with the development of precision agriculture systems. The nonlinear variations of pixel intensity with illuminationand other causes such as blurs and poor video quality also...

article

Self‐adaptive‐deer hunting optimization‐based optimal weighted features and hybrid classifier for automated disease detection in plant leaves

Kalicharan Sahu, Sonajharia Minz

Expert Systems > 39 > 7 > n/a - n/a

This main intention of this paper is to adopt a new disease detection model for plant leaves. The proposed model involves several steps such as pre‐processing, leaf segmentation, abnormality segmentation, feature extraction and detection. Image scaling and contrast enhancement are performed during the pre‐processing phase. Once the pre‐processing is done, the segmentation phase starts with leaf segmentation...

article

An accurate foreground moving object detection based on segmentation techniques and optimal classifier

Melam Nagaraju, B. Sobhan Babu, Meduri V. N. S. S. R. K. Sai Somayajulu, K. Subrahmanya Kousik Sarma, more

Concurrency and Computation: Practice and Experience > 34 > 5 > n/a - n/a

In video surveillance schemes, the motion object detection plays a significant role. To subtract the object background, a segmentation technique based on feature extraction is utilized in which the change in the training rate makes an alteration in the background. Thereafter, the extracted features are trained by using the self‐organizing map (SOM) network in which the weight parameters in the network...

article

Glioma grade detection using grasshopper optimization algorithm‐optimized machine learning methods: The Cancer Imaging Archive study

Mohammadreza Hedyehzadeh, Keivan Maghooli, Mohammad MomenGharibvand

International Journal of Imaging Systems and Technology > 31 > 3 > 1670 - 1677

Detection of brain tumor's grade is a very important task in treatment plan design which was done using invasive methods such as pathological examination. This examination needs resection procedure and resulted in pain, hemorrhage and infection. The aim of this study is to provide an automated non‐invasive method for estimation of brain tumor's grade using Magnetic Resonance Images (MRI). After pre‐processing,...

article

Local binary pattern encoding schemes for computed tomography image segmentation: An experimental and comparative study

Hsien‐Jen Lo, Chih‐Hung Wu

International Journal of Imaging Systems and Technology > 31 > 3 > 1300 - 1316

Local binary patterns (LBPs) are used for effective texture representation in various applications. This study explores the clustering consistency and stability of image segmentation when distance‐based clustering methods are used with an LBP. Because data are described by features and attributes, distances among data are also dominated by the definition of features. Moreover, four popular LBP encoding...

article

Modified deep belief network based human emotion recognition with multiscale features from video sequences

Velagapudi Sreenivas, Varsha Namdeo, Eda Vijay Kumar

Software: Practice and Experience > 51 > 6 > 1259 - 1279

Emotion recognition from human faces are recently considered as growing topic for the applications in HCI (human–computer interaction) field. Therefore, a new framework is introduced in this method for emotion recognition from video. Human faces may carry huge features which increase the complexity of recognizing the emotions from the give video. Therefore, to minimize such defect, the wrapper based...

article

Rgb-D face recognition using LBP-DCT algorithm

Sunil B L Kumar, Sharmila M Kumari

Applied Computer Science > 2021 > Vol. 17, no 3 > 73--81

Face recognition is one of the applications in image processing that recognizes or checks an individual's identity. 2D images are used to identify the face, but the problem is that this kind of image is very sensitive to changes in lighting and various angles of view. The images captured by 3D camera and stereo camera can also be used for recognition, but fairly long processing times is needed. RGB-D...

article

Detection of sunn pest‐damaged wheat grains using artificial bee colony optimization‐based artificial intelligence techniques

Kadir Sabanci

Journal of the Science of Food and Agriculture > 100 > 2 > 817 - 824

BACKGROUND In this study, artificial intelligence models that identify sunn pest‐damaged wheat grains (SDG) and healthy wheat grains (HWG) are presented. Svevo durum wheat cultivated in Konya province, Turkey is used for the process, with 150 HWG and 150 SDG being used for classification. Thanks to the constructed imaging setup, photos of the 300 wheat grains are obtained. Seventeen visual features...

article

Hybrid feature vector based detection of Glaucoma

Nirmala Krishnamoorthi, Vinoth Kumar Chinnababu

Multimedia Tools and Applications > 2019 > 78 > 24 > 34247- 34276

This paper focus on the investigation of the potential in retinal image analysis for the detection of Glaucoma. The computer-based analysis of the parameter involves the use of image processing algorithms for pre-processing, localization and segmentation of the region of interest (ROI), feature extraction from ROI, and classification. The initial step in computer based detection system includes the...

article

Detection of Moving Object in Dynamic Visual Sequences Based on Partial Least Squares Classifier

Shyamala Balakumar, Selvaperumal Sundaramoorthy, Ramasubramanian Bhoopalan, G. Prabhakar

Journal of Medical Systems > 2019 > 43 > 8 > 1-8

Detection of moving object from a visual sequence plays a vital role for the tracking of object. The main objective of this proposed work is to detect and classify the various video sequences with the help of different classification algorithms. The input video sequences from the publicly available datasets are collected and the individual frames are extracted. These frames are pre-processed and then...

article

Towards large-scale face-based race classification on spark framework

Mezzoudj Saliha, Behloul Ali, Seghir Rachid

Multimedia Tools and Applications > 2019 > 78 > 18 > 26729- 26746

Recently, the identification of an individual race has become an important research topic in face recognition systems, especially in large-scale face images. In this paper, we propose a new large-scale race classification method which combines Local Binary Pattern (LBP) and Logistic Regression (LR) on Spark framework. LBP is used to extract features from facial images, while spark’s logistic regression...

article

Brain disease diagnosis using local binary pattern and steerable pyramid

Vandana V. Kale, Satish T. Hamde, Raghunath S. Holambe

International Journal of Multimedia Information Retrieval > 2019 > 8 > 3 > 155-165

Brain diseases can cause invisible disorders, cognitive and behavioral changes. Their symptoms vary widely. In some cases, treatment can improve the symptoms while in other cases injuries become permanent. Many disorders are progressive. Therefore, early and accurate diagnosis of disorder is essential for improving disorder condition and patient’s quality of life. This paper presents the brain disease...

article

Local binary pattern-based discriminant graph construction for dimensionality reduction with application to face recognition

Bo Yang, Qian-zhong Li

Multimedia Tools and Applications > 2019 > 78 > 16 > 22445- 22462

Graph construction has attracted increasing interest in recent years due to its key role in many dimensionality reduction (DR) algorithms. On the other hand, our previous study shows that the Local-Binary-Pattern Image (LBPI) representation is a more powerful discriminant and is invariant to monotonic gray level changes. Here, we attempt to construct a discriminant graph for DR in the LBPI representation...

article

Texture Feature Extraction from Thyroid MR Imaging Using High-Order Derived Mean CLBP

Zhe Liu, Cheng-Jian Qiu, Yu-Qing Song, Xiao-Hong Liu, more

Journal of Computer Science and Technology > 2019 > 34 > 1 > 35-46

In the field of medical imaging, the traditional local binary pattern (LBP) and its improved algorithms are often sensitive to noise. Traditional LBPs are solely based on the signal information from local differences, and the binary quantization method oversimplifies the local texture features while disregarding the imaging information from the concaveconvex regions between the high-order pixels and...

article

Detection of Modic changes in MR images of spine using local binary patterns

Jiyo S. Athertya, Gurunathan Saravana Kumar, Jayaraj Govindaraj

Biocybernetics and Biomedical Engineering > 2019 > Vol. 39, no. 1 > 17--29

Background and objective: With increase in prevalence of lower back pain, fast and reliable computer aided methods for clinical diagnosis associated with the same is needed for improving the healthcare reach. The magnetic resonance images exhibit a change in signal intensity on the vertebral body close to end plates, which are termed as Modic changes (MC), and are known to be clear indicators of lower...

article

Local Neighborhood Intensity Pattern–A new texture feature descriptor for image retrieval

Prithaj Banerjee, Ayan Kumar Bhunia, Avirup Bhattacharyya, Partha Pratim Roy, more

Expert Systems with Applications > 2018 > 113 > C > 100-115

In this paper, a new texture descriptor based on the local neighborhood intensity difference is proposed for content based image retrieval (CBIR). For computation of texture features like Local Binary Pattern (LBP), the center pixel in a 3 × 3 window of an image is compared with all the remaining neighbors, one pixel at a time to generate a binary bit pattern. It ignores the effect of the adjacent...

article

Gender classification from face images by mixing the classifier outcome of prime, distinct descriptors

A. Geetha, M. Sundaram, B. Vijayakumari

Soft Computing > 2019 > 23 > 8 > 2525-2535

Since the last decade, the area of recognizing gender of a person from an image of his/her face has been playing an important role in the research field. A automatic gender recognition is an important concept, essential for many fields like forensic science and automatic payment system. However, it is very onerous due to high variability factors such as illumination, expression, pose, age, scales,...

article

Local mean differential excitation pattern for content based image retrieval

G. V. Satya Kumar, P. G. Krishna Mohan

SN Applied Sciences > 2019 > 1 > 1 > 1-10

Effective and facile local texture feature descriptors assume a significant role in many image classification and retrieval tasks. However, conventional feature descriptors are impaired to capture salient image features like local inherent structure, orientation and edge information of the image. A typical local binary pattern (LBP)-like feature descriptors elicits information based on the gray level...

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Search results

LBP and Weber law descriptor feature based CRF model for detection of man-made structures

Face recognition based on curvelets and local binary pattern features via using local property preservation

Hybrid texture and gradient modeling for dynamic background subtraction identification systemin tobacco plant using 5G data service

Self‐adaptive‐deer hunting optimization‐based optimal weighted features and hybrid classifier for automated disease detection in plant leaves

An accurate foreground moving object detection based on segmentation techniques and optimal classifier

Glioma grade detection using grasshopper optimization algorithm‐optimized machine learning methods: The Cancer Imaging Archive study

Local binary pattern encoding schemes for computed tomography image segmentation: An experimental and comparative study

Modified deep belief network based human emotion recognition with multiscale features from video sequences

Rgb-D face recognition using LBP-DCT algorithm

Detection of sunn pest‐damaged wheat grains using artificial bee colony optimization‐based artificial intelligence techniques

Hybrid feature vector based detection of Glaucoma

Detection of Moving Object in Dynamic Visual Sequences Based on Partial Least Squares Classifier

Towards large-scale face-based race classification on spark framework

Brain disease diagnosis using local binary pattern and steerable pyramid

Local binary pattern-based discriminant graph construction for dimensionality reduction with application to face recognition

Texture Feature Extraction from Thyroid MR Imaging Using High-Order Derived Mean CLBP

Detection of Modic changes in MR images of spine using local binary patterns

Local Neighborhood Intensity Pattern–A new texture feature descriptor for image retrieval

Gender classification from face images by mixing the classifier outcome of prime, distinct descriptors

Local mean differential excitation pattern for content based image retrieval

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