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Search Results (112)
  • Open Access

    ARTICLE

    A Novel Ego Lanes Detection Method for Autonomous Vehicles

    Bilal Bataineh*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1941-1961, 2023, DOI:10.32604/iasc.2023.039868

    Abstract Autonomous vehicles are currently regarded as an interesting topic in the AI field. For such vehicles, the lane where they are traveling should be detected. Most lane detection methods identify the whole road area with all the lanes built on it. In addition to having a low accuracy rate and slow processing time, these methods require costly hardware and training datasets, and they fail under critical conditions. In this study, a novel detection algorithm for a lane where a car is currently traveling is proposed by combining simple traditional image processing with lightweight machine learning (ML) methods. First, a preparation… More >

  • Open Access

    ARTICLE

    Melanoma Detection Based on Hybridization of Extended Feature Space

    Anuj Kumar, Shakti Kumar*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2175-2198, 2023, DOI:10.32604/iasc.2023.039093

    Abstract Melanoma is a perfidious form of skin cancer. The study offers a hybrid framework for the automatic classification of melanoma. An Automatic Melanoma Detection System (AMDS) is used for identifying melanoma from the infected area of the skin image using image processing techniques. A larger number of pre-existing automatic melanoma detection systems are either commercial or their accuracy can be further improved. The research problem is to identify the best preprocessing technique, feature extractor, and classifier for melanoma detection using publically available MED-NODE data set. AMDS goes through four stages. The preprocessing stage is for noise removal; the segmentation stage… More >

  • Open Access

    ARTICLE

    Shadow detection and correction using a combined 3D GIS and image processing approach

    Safa Ridene1 , Reda Yaagoubi1, Imane Sebari1, Audrey Alajouanine2

    Revue Internationale de Géomatique, Vol.29, No.3, pp. 241-253, 2019, DOI:10.3166/rig.2019.00091

    Abstract While shadow can give useful information about size and shape of objects, it can pose problems in feature detection and object detection, thereby, it represents one of the major perturbator phenomenons frequently occurring on images and unfortunately, it is inevitable. “Shadows may lead to the failure of image analysis processes and also cause a poor quality of information which in turn leads to problems in implementation of algorithms.” (Mahajan and Bajpayee, 2015). It also affects multiple image analysis applications, whereby shadow cast by buildings deteriorate the spectral values of the surfaces. Therefore, its presence causes a deterioration in the visual… More >

  • Open Access

    ARTICLE

    Fuzzy Rule-Based Model to Train Videos in Video Surveillance System

    A. Manju1, A. Revathi2, M. Arivukarasi1, S. Hariharan3, V. Umarani4, Shih-Yu Chen5,*, Jin Wang6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 905-920, 2023, DOI:10.32604/iasc.2023.038444

    Abstract With the proliferation of the internet, big data continues to grow exponentially, and video has become the largest source. Video big data introduces many technological challenges, including compression, storage, transmission, analysis, and recognition. The increase in the number of multimedia resources has brought an urgent need to develop intelligent methods to organize and process them. The integration between Semantic link Networks and multimedia resources provides a new prospect for organizing them with their semantics. The tags and surrounding texts of multimedia resources are used to measure their semantic association. Two evaluation methods including clustering and retrieval are performed to measure… More >

  • Open Access

    ARTICLE

    Dual-Branch-UNet: A Dual-Branch Convolutional Neural Network for Medical Image Segmentation

    Muwei Jian1,2,#,*, Ronghua Wu1,#, Hongyu Chen1, Lanqi Fu3, Chengdong Yang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 705-716, 2023, DOI:10.32604/cmes.2023.027425

    Abstract In intelligent perception and diagnosis of medical equipment, the visual and morphological changes in retinal vessels are closely related to the severity of cardiovascular diseases (e.g., diabetes and hypertension). Intelligent auxiliary diagnosis of these diseases depends on the accuracy of the retinal vascular segmentation results. To address this challenge, we design a Dual-Branch-UNet framework, which comprises a Dual-Branch encoder structure for feature extraction based on the traditional U-Net model for medical image segmentation. To be more explicit, we utilize a novel parallel encoder made up of various convolutional modules to enhance the encoder portion of the original U-Net. Then, image… More >

  • Open Access

    REVIEW

    An Overview of Double JPEG Compression Detection and Anti-detection

    Kun Wan*

    Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 89-101, 2022, DOI:10.32604/jihpp.2022.039764

    Abstract JPEG (Joint Image Experts Group) is currently the most widely used image format on the Internet. Existing cases show that many tampering operations occur on JPEG images. The basic process of the operation is that the JPEG file is first decompressed, modified in the null field, and then the tampered image is compressed and saved in JPEG format, so that the tampered image may be compressed several times. Therefore, the double compression detection of JPEG images can be an important part for determining whether an image has been tampered with, and the study of double JPEG compression anti-detection can further… More >

  • Open Access

    ARTICLE

    Semantic Document Layout Analysis of Handwritten Manuscripts

    Emad Sami Jaha*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2805-2831, 2023, DOI:10.32604/cmc.2023.036169

    Abstract A document layout can be more informative than merely a document’s visual and structural appearance. Thus, document layout analysis (DLA) is considered a necessary prerequisite for advanced processing and detailed document image analysis to be further used in several applications and different objectives. This research extends the traditional approaches of DLA and introduces the concept of semantic document layout analysis (SDLA) by proposing a novel framework for semantic layout analysis and characterization of handwritten manuscripts. The proposed SDLA approach enables the derivation of implicit information and semantic characteristics, which can be effectively utilized in dozens of practical applications for various… More >

  • Open Access

    ARTICLE

    Identification of a Printed Anti-Counterfeiting Code Based on Feature Guidance Double Pool Attention Networks

    Changhui You1,2, Hong Zheng1,2,*, Zhongyuan Guo2, Tianyu Wang2, Jianping Ju3, Xi Li3

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3431-3452, 2023, DOI:10.32604/cmc.2023.035897

    Abstract The authenticity identification of anti-counterfeiting codes based on mobile phone platforms is affected by lighting environment, photographing habits, camera resolution and other factors, resulting in poor collection quality of anti-counterfeiting codes and weak differentiation of anti-counterfeiting codes for high-quality counterfeits. Developing an anti-counterfeiting code authentication algorithm based on mobile phones is of great commercial value. Although the existing algorithms developed based on special equipment can effectively identify forged anti-counterfeiting codes, the anti-counterfeiting code identification scheme based on mobile phones is still in its infancy. To address the small differences in texture features, low response speed and excessively large deep learning… More >

  • Open Access

    ARTICLE

    Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

    Tarique Rafique Memon1,2,*, Tayab Din Memon3,4, Imtiaz Hussain Kalwar5, Bhawani Shankar Chowdhry1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2461-2477, 2023, DOI:10.32604/cmc.2023.035413

    Abstract Derailment of trains is not unusual all around the world, especially in developing countries, due to unidentified track or rolling stock faults that cause massive casualties each year. For this purpose, a proper condition monitoring system is essential to avoid accidents and heavy losses. Generally, the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment. Therefore, in this paper, we present the development of a novel embedded system prototype for condition monitoring of railway track. The proposed prototype system works in real-time by acquiring railway… More >

  • Open Access

    ARTICLE

    Novel Vegetation Mapping Through Remote Sensing Images Using Deep Meta Fusion Model

    S. Vijayalakshmi*, S. Magesh Kumar

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2915-2931, 2023, DOI:10.32604/iasc.2023.034165

    Abstract Preserving biodiversity and maintaining ecological balance is essential in current environmental conditions. It is challenging to determine vegetation using traditional map classification approaches. The primary issue in detecting vegetation pattern is that it appears with complex spatial structures and similar spectral properties. It is more demandable to determine the multiple spectral analyses for improving the accuracy of vegetation mapping through remotely sensed images. The proposed framework is developed with the idea of ensembling three effective strategies to produce a robust architecture for vegetation mapping. The architecture comprises three approaches, feature-based approach, region-based approach, and texture-based approach for classifying the vegetation… More >

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