Results 201 to 210 of about 15,845 (235)

Texture description using multi-scale morphological GLCM

Multimedia Tools and Applications, 2018
Texture is the collective repetitive pattern that characterizes the surface of real world objects. The main challenge in the texture description is its application specific definition. The present work aims at bringing the definition of textures under a generalized framework and propose some texture descriptors.
Mudassir Rafi, Susanta Mukhopadhyay
openaire   +1 more source

Texture segmentation using different orientations of GLCM features

Proceedings of the 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications, 2013
This paper describes the development of a new texture based segmentation algorithm which uses a set of features extracted from Grey-Level Co-occurrence Matrices. The proposed method segments different textures based on noise reduced features which are effective texture descriptor.
Andrik Rampun, Harry Strange, Reyer Zwiggelaar   +2 more
openaire   +1 more source

The Combine of GLCM and Group, Focuses on the Grayscale of Medical Images

2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Medical image classification is very important in the diagnosis of hepatocellular carcinoma, which can provide more accurate computer-aided diagnosis, and accurate extraction of key semantic information from medical data is crucial to improve classification performance.
Zechen Zheng, Chao Fan, Congqian Wang, Miao Wang, Lizhi Zhang, Xiaowei He 0001, Xuelei He   +6 more
openaire   +2 more sources

GLCM and neural network-based watermark identification

SPIE Proceedings, 2008
In this work, we extend our previous research on gray level co-occurrence matrix (GLCM) based watermark embedding in the discrete cosine transform (DCT) domain to the discrete wavelet transform (DWT) domain. The GLCM method incorporated human visual system information into the embedding process making the watermark more transparent.
Lifford McLauchlan, Mehrübe Mehrübeoğlu   +1 more
openaire   +1 more source

Smoke detection using GLCM, wavelet, and motion

SPIE Proceedings, 2014
This paper presents a supervised smoke detection method that uses local and global features. This framework integrates and extends notions of many previous works to generate a new comprehensive method. First chrominance detection is used to screen areas that are suspected to be smoke. For these areas, local features are then extracted. The features are
Teerasak Srisuwan, Miti Ruchanurucks
openaire   +1 more source

GLCM texture classification for EEG spectrogram image

2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2010
Over the past century, time based and frequency based is used for analyzing Electroencephalography (EEG) signals. EEG is a scientific tool for measure signal from human brain. This paper proposes a time-frequency approach or spectrogram image processing technique for analyzing EEG signals.
Mahfuzah Mustafa, null Mohd Nasir Taib, Zunairah Hj. Murat, null Noor Hayatee Abdul Hamid   +3 more
openaire   +1 more source

Blind Image Quality Assessment via Analysis of GLCM

2018
Blind image quality assessment (BIQA) assesses the perceptual quality of the distorted image without any information about its original reference image. Features, in consistent with human visual system (HVS), have been proved effective for BIQA. Motivated by this, we propose a novel general purpose BIQA approach.
Guanghui Yue 0001, Chunping Hou, Tongtong Ma, Yang Yang 0045   +3 more
openaire   +1 more source

DCT based texture watermarking using GLCM

2010 IEEE 2nd International Advance Computing Conference (IACC), 2010
We present a novel DCT technique for digital watermarking of textured images based on the concept of gray-level co-occurrence matrix (GLCM). We provide analysis to describe the behavior of the method in terms of correlation as a function of the offset for textured images.
Sushila Kamble, Suneeta Agarwal, V.K. Shrivastava, Vikas Maheshkar   +3 more
openaire   +1 more source

การเปรียบเทียบการจำแนกเชิงวัตถุข้อมูลดาวเทียม SPOT 5 จากการวิเคราะห์ค่าการสะท้อนแสงและลายเนื้อชนิด GLCM

การจำแนกข้อมูลดาวเทียมด้วยเทคนิคการจำแนกเชิงวัตถุ (Object-based classification) ช่วยจำแนกวัตถุบนภาพถ่ายจากค่าการสะท้อนแสง (Spectral analysis) ให้มีความถูกต้องดียิ่งขึ้น แต่การจำแนกพืชที่ปลูกในบริเวณใกล้เคียงกันและมีค่าการสะท้อนแสงใกล้เคียงกันยังคงทำให้การจำแนกข้อมูลมีการปะปนกัน การใช้อัลกอริธึมลายเนื้อ (Texture algorithm) ชนิด Gray Level Co-occurrence ...
openaire   +1 more source

Blurred image recognition based on GLCM

5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 2023
Yan Li, Jinqiao Du, Yong Yi, Jie Tian, Zijun Liu, Yuhuan Li, Fan Yang   +6 more
openaire   +1 more source