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International conference on Advanced Communication Control and Computing Technologies

作者： P.Ravivarma B. Ramasubramanian G.Arunmani B.Babumohan Assistant Professor Department of ECESyed Ammal Engineering CollegeTamilNadu India

ISBN: (纸本)9781479939152

Diabetic Retinopathy is the major cause of blindness in many diabetic patients. Automatic detection of exudates in retinal images can assist in early screening of Diabetic Retinopathy. Several techniques can achieve good performance on a good quality retinal images. But when the image is of low quality, we need a new method. In this paper, we presented a novel method for the detection of exudates in low quality retinal images. The colour retinal images are pre-processed by a hyperbolic median filter and then segmented using fuzzy c- means clustering algorithm. After segmenting the images, a set of features based on colour, size and texture are extracted. Then these features are optimized using Particle Swarm Optimization (PSO) technique. Finally the features are classified using a recursive Support Vector Machine (SVM) Classifier. The proposed method achieves an accuracy of 98% and predictivity of 98.5% for the identification of exudates.

关键词： Diabetic Retinopathy Fuzzy C-means GLCM PSO rSVM

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Segmentation of humeral head from MR slices

Segmentation of humeral head from MR slices

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ieee Signal processing and communications Applications (SIU)

作者： Aysun Sezer Hasan Basri Sezer Songül Albayrak Yildiz Teknik Universitesi Istanbul TR Cicli Hamidiye Etfal Eğitim ve Araştırma Hastanesi Ortopedi Bölümü İstanbul Türkiye

The purpose of this study is to segment the humeral head from two dimentional proton dansity(PD) magnetic resonance images (MRI) of shoulder. MRI studies of patients presenting with shoulder pain may demonstrate bone marrow edema and different degrees of contour changes. Computerised tomography(CT) and T1 weighted MR images demonstrate bone margins better. T2 or PD weighted images are poor in determining exact images of bone margins, instead they give better detection of edema and thus pathology. However PD weighted slices have a higher noise to signal ratio than other modalities. Moreover soft tissues in close proximity to humeral head which have the similar intensity with bone make the segmentation of bony humeral head a challenging problem in PD weighted images. In this study we used a new data set which consists of PD weighted axial images of 33 shoulder MRI examinations of 33 randomly selected patients. We used specle reducing anisotropic diffusion(SRAD) method to decrease noise in PD weigted images. Secondly using Hough transform the round shaped humeral head was located roughly, afterwards for a more successful segmentation we applied active contour without edge (ACWE) method. Success of these methods is determined by comparing our results with manual segmentaion results of an expert and evaluated by Sorensen-Dice metric. The average value of measure over the entire database is found to be 90% by ACWE method. Application of ACWE method on PD weighted images provided higly successfull results for segmentation of bony structures. There is no other study to de determine bone contours in PD images in the literature.

关键词： image segmentation Active contours conferences image edge detection Magnetic resonance imaging Object segmentation Signal processing

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Hybrid wavelet - DCT intra prediction for H.264/AVC interactive encoder

Hybrid wavelet - DCT intra prediction for H.264/AVC interact...

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ieee China Summit & International conference on Signal and Information processing (ChinaSIP)

作者： T. Elarabi A. Sammoud A. Abdelgawad X. Li M. Bayoumi The Center for Advanced Computer Studies (CACS) University of Louisiana at Lafayette (UL Lafayette) LA USA Central Michigan University

With the growing usage of mobile video applications and Internet based video services; techniques and algorithms of the current video compression standards face new challenging demands for lower bit-rate and faster processing speed. H.264/AVC video compression standard is widely used and provides state of the art video compression solution, but still needs to address the challenges of high bit-rate and required processing power. In this paper, a low bit-rate compression algorithm is proposed, which introduces a novel approach that use both DCT (Discrete Cosine Transform) and DWT (Discrete Wavelet Transform) for enhancing the Intra-Prediction phase of H.264/AVC standard. The proposed Hybrid Wavelet-DCT (HW-DCT) algorithm modifies the FSF (Full Search Free) algorithm; by adding wavelet-based transformation prior to the Intra-prediction process. The HW-DCT algorithm adds up the advantages of wavelet based compression technique to the speed of the FSF algorithm and creates an Intra-prediction algorithm that guarantees 51% lower bit-rate while maintaining similar visual quality and Peak Signal to Noise Ratio (PSNR) of the original H.264/AVC Intra-prediction algorithm. The JM 18.2 Reference software implementation results have validated the effectiveness of our proposed algorithm and shown a significant improvements in both run-time and bit-rate.

关键词： Video coding Prediction algorithms image coding Standards Wavelet transforms Discrete cosine transforms Software algorithms

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Enhanced Skin Lesion Classification Using CNN and Fine-Tuned VGG16 Model

Enhanced Skin Lesion Classification Using CNN and Fine-Tuned...

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Intelligent Signal processing and Effective Communication Technologies (INSPECT), ieee International conference on

作者： Deepak Chauhan Aviral Sharma Abhinay Verma Dharmender Singh Kushwaha Computer Science and Engineering MNNIT Allahabad Prayagraj Department Of Computer Science and Engineering MNNIT Allahabad Prayagraj

ISBN: (数字)9798350379525

ISBN: (纸本)9798350379532

Skin cancer is a prevalent form of cancer globally, necessitating accurate and early diagnosis. Leveraging deep learning, particularly Convolutional Neural Networks (CNNs), has shown promise in dermatological applications. This paper presents a skin lesion classification approach using VGG 16, enhanced through fine-tuning for dermoscopic images, extensive data augmentation, and a weighted loss function to address dataset imbalance and improve performance on minority classes. It also utilizes a balanced dataset from the HAM10000. VGG16 is a widely recognized convolutional neural network (CNN) architecture, designed by the visual Geometry Group at the University of Oxford. It gained prominence for its outstanding performance in image classification during the 2014 imageNet Large Scale visual Recognition Challenge(ILSVRC). We utilize the pretrained VGG16 model's initial weights as the starting point for the convolutional layers in our proposed architecture. The experiments are conducted on an Nvidia T4×2 GPU to accelerate the results. The proposed model achieved an accuracy of 85.12 % for skin lesion classification.

关键词： Deep learning visualization Accuracy image recognition Skin Lesions Convolutional neural networks Medical diagnostic imaging image classification Skin cancer

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Implementation of real-time object recognition system for home-service robot by integrating SURF and BRISK

Implementation of real-time object recognition system for ho...

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International conference on System Science and Engineering (ICSSE)

作者： Hsuan Lee Chih-Yin Liu Chih-Jui Lin Chien-Feng Huang Ri-Wei Deng Tzuu-Hseng S. Li Department of Electrical Engineering National Cheng Kung University Tainan ROC Taiwan

This paper proposes a real-time object recognition systems for recognizing known objects and searching unknown objects for home service robot. The object recognition system is mainly used in recognizing known objects, which combined Compute Unified Device Architecture (CUDA), Speeded Up Robust Features (SURF) detector and Binary Robust Invariant Scalable Keypoints (BRISK) descriptor for improving the computation speed and decreasing the consumption on memory. On the other side, the visual perception system is usually used for searching unknown objects, which calculated the depth differences and found the contours of objects. The experimental results in the laboratory and the competition in robot@home league at RoboCup Japan Open 2013 Tokyo illustrate that the robot can successfully real-time recognize the known objects and search the unknown objects.

关键词： Real-time systems image recognition Search problems Speech Graphics processing units Three-dimensional displays Acoustics

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3D shape reconstruction from a humanoid generated video sequence

3D shape reconstruction from a humanoid generated video sequ...

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ieee-RAS International conference on Humanoid Robots

作者： P. A. Martínez D. Varas M. Castelán M. Camacho F. Marques G. Arechavaleta Robotics and Advanced Manufacturing Group Centro de Investigación y Estudios Avanzados del Instituto Politécnico Nacional Ramos Arizpe Coah México Department of Signal Theory and Communications Universitat Politècnica de Catalunya Barcelona Spain

This paper presents a strategy for estimating the geometry of an interest object from a monocular video sequence acquired by a walking humanoid robot. The problem is solved using a space carving algorithm, which relies on both the accurate extraction of the occluding boundaries of the object as well as the precise estimation of the camera pose for each video frame. For data acquisition, a monocular visual-based control has been developed that drives the trajectory of the robot around an object placed on a small table. Due to the stepping of the humanoid, the recorded sequence is contaminated with artefacts that affect the correct extraction of contours along the video frames. To overcome this issue, a method that assigns a fitness score for each frame is proposed, delivering a subset of camera poses and video frames that produce consistent 3D shape estimations of the objects used for experimental evaluation.

关键词： Cameras Three-dimensional displays Robot vision systems Shape Trajectory image reconstruction

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Review of, "Advances for In-Vehicle and Mobile Systems" [Book Review]

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ieee Intelligent Transportation Systems Magazine 2014年第4期6卷 78-79页

作者： Christos-Nikolaos E. Anagnostopoulos Faculty of Mathematics and Mechanics St. Petersburg State University St. Petersburg Russia

The focus of this book (with invited papers from an International conference) is to bring together the most active scholars working on the latest techniques, standards, and emerging deployment of wireless communications and smart vehicular systems. The objective is the successful fusion of speech, dialog, video, image, vehicular sensory data and wireless communication modalities in order to model driver's behavior and use that model towards personalization of the vehicle to provide a more comfortable and safer driving environment. The book is divided in four parts: 1) driver and driving environment recognition, 2) telecommunication applications, 3) noise reduction and 4) dialog in vehicles.

关键词： Book reviews Intelligent vehicles Mobile communication Noise reduction Speech enhancement Digital signal processing

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High quality, low latency in-home streaming of multimedia applications for mobile devices

High quality, low latency in-home streaming of multimedia ap...

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Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Daniel Pohl Stefan Nickels Ram Nalla Oliver Grau Intel Labs Intel Corporation Intel Visual Computing Institute Saarland University Saarbrücken

Today, mobile devices like smartphones and tablets are becoming more powerful and exhibit enhanced 3D graphics performance. However, the overall computing power of these devices is still limited regarding usage scenarios like photo-realistic gaming, enabling an immersive virtual reality experience or real-time processing and visualization of big data. To overcome these limitations application streaming solutions are constantly gaining focus. The idea is to transfer the graphics output of an application running on a server or even a cluster to a mobile device, conveying the impression that the application is running locally. User inputs on the mobile client side are processed and sent back to the server. The main criteria for successful application streaming are low latency, since users want to interact with the scene in near real-time, as well as high image quality. Here, we present a novel application framework suitable for streaming applications from high-end machines to mobile devices. Using real-time ETC1 compression in combination with a distributed rendering architecture we fully leverage recent progress in wireless computer networking standards (ieee 802.11ac) for mobile devices, achieving much higher image quality at half the latency compared to other inhome streaming solutions.

关键词： Streaming media Servers Rendering (computer graphics) image coding image quality Mobile handsets Games

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Investigating Local Spatially-Enhanced Structural and Textural Descriptors for Classification of iPSC Colony images

Investigating Local Spatially-Enhanced Structural and Textur...

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Annual International conference of the ieee Engineering in Medicine and Biology Society

作者： Yulia Gizatdinova Jyrki Rasku Markus Haponen Henry Joutsijoki Ivan Baldin Michelangelo Paci Jari Hyttinen Katriina Aalto-Setala Martti Juhola School of Information Sciences University of Tampere Institute of Biomedical Technology University of Tampere Department of Electronics and Communications Engineering Tampere University of Technology

ISBN: (纸本)9781424479276

Induced pluripotent stem cells (iPSC) can be derived from fully differentiated cells of adult individuals and used to obtain any other cell type of the human body. This implies numerous prospective applications of iPSCs in regenerative medicine and drug development. In order to obtain valid cell culture, a quality control process must be applied to identify and discard abnormal iPSC colonies. Computer vision systems that analyze visual characteristics of iPSC colony health can be especially useful in automating and improving the quality control process. In this paper, we present an ongoing research that aims at the development of local spatially-enhanced descriptors for classification of iPSC colony images. For this, local oriented edges and local binary patterns are extracted from the detected colony regions and used to represent structural and textural properties of the colonies, respectively. We preliminary tested the proposed descriptors in classifying iPSCs colonies according to the degree of colony abnormality. The tests showed promising results for both, detection of iPSC colony borders and colony classification.

关键词： Histograms visualization image edge detection Shape Support vector machines Feature extraction Stem cells

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Randomized Max-Margin Compositions for visual Recognition

Randomized Max-Margin Compositions for Visual Recognition

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ieee conference on Computer Vision and Pattern Recognition

作者： Angela Eigenstetter Masato Takami Bjorn Ommer Heidelberg Collaboratory for Image Processing & IWR University of Heidelberg

ISBN: (纸本)9781479951192

A main theme in object detection are currently discriminative part-based models. The powerful model that combines all parts is then typically only feasible for few constituents, which are in turn iteratively trained to make them as strong as possible. We follow the opposite strategy by randomly sampling a large number of instance specific part classifiers. Due to their number, we cannot directly train a powerful classifier to combine all parts. Therefore, we randomly group them into fewer, overlapping compositions that are trained using a maximum-margin approach. In contrast to the common rationale of compositional approaches, we do not aim for semantically meaningful ensembles. Rather we seek randomized compositions that are discriminative and generalize over all instances of a category. Our approach not only localizes objects in cluttered scenes, but also explains them by parsing with compositions and their constituent parts. We conducted experiments on PASCAL VOC07, on the VOC10 evaluation server, and on the MITIndoor scene dataset. To the best of our knowledge, our randomized max-margin compositions (RM~2C) are the currently best performing single class object detector using only HOG features. Moreover, the individual contributions of compositions and their parts are evaluated in separate experiments that demonstrate their potential.

关键词： Training visualization Object detection Object recognition Support vector machines Deformable models Pattern recognition

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