Evolutionary improved object detector for ultrasound images

Masek, Jan; Bürget, Radim; Karasek, Jan; Uher, Václav; Güney, Selda

doi:10.1109/tsp.2013.6614002

Cited by 14 publications

(4 citation statements)

References 13 publications

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“…Modified versions of Viola-Jones algorithms can be used for object detection in noisy ultrasound images. The paper [2] describes detection of carotid artery longitudinal section in ultrasound B-mode images.…”

Section: Viola-jones Algorithmsmentioning

confidence: 99%

Real-time face tracking in video content using Viola-Jones algorithm

Doric¹,

Crnobrnja²,

Punt³

et al. 2019

Telfor J

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Section: Viola-jones Algorithmsmentioning

confidence: 99%

Real-time face tracking in video content using Viola-Jones algorithm

Doric¹,

Crnobrnja²,

Punt³

et al. 2019

Telfor J

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“…OpenCV based on Haar cascade Classifier have been used. Haar cascade classifiers were also used in object detection in ultrasound images [8] and the detector was trained by AdaBoost algorithm. Detection was 96.29% successful compared to SVM classification result in paper [8].…”

Section: Related Workmentioning

confidence: 99%

“…Haar cascade classifiers were also used in object detection in ultrasound images [8] and the detector was trained by AdaBoost algorithm. Detection was 96.29% successful compared to SVM classification result in paper [8]. A significant attention was grown to vehicle detection and various filter algorithms were primary focus for detection of vehicles.…”

Section: Related Workmentioning

confidence: 99%

Performance analysis of a surveillance system to detect and track vehicles using Haar cascaded classifiers and optical flow method

Noor

Siddiquee

Sarma

et al. 2017

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)

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This paper presents the real time vehicle detection and tracking system, based on data, collected from a single camera. In this system, vehicles are detected by using Haar Feature-based Cascaded Classifier on static images, extracted from the video file. The advantage of this classifier is that, it uses floating numbers in computations and hence, 20% more accuracy can be achieved in comparison to other classifiers and features of classifiers such as LBP (Local Binary Pattern). Tracking of the vehicles is carried out using Lucas-Kanade and Horn Schunk Optical Flow method because it performs better than other methods such as Morphological and Correlation Transformations. The proposed system consists of vehicle detection and tracking; and it is evaluated by using real data, collected from the route networks of Chittagong City of Bangladesh.

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“…That said, methods based on feature extraction and engineering (hand-crafted features) continue to be commonly used across CV tasks such as object detection and localisation, and segmentation. For example, in [24] ,the authors used a modified version of Viola…”

Section: Introductionmentioning

confidence: 99%

Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward

Elyan¹,

Vuttipittayamongkol²,

Johnston³

et al. 2022

Art Int Surg

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The recent development in the areas of deep learning and deep convolutional neural networks has significantly progressed and advanced the field of computer vision (CV) and image analysis and understanding. Complex tasks such as classifying and segmenting medical images and localising and recognising objects of interest have become much less challenging. This progress has the potential of accelerating research and deployment of multitudes of medical applications that utilise CV. However, in reality, there are limited practical examples being physically deployed into front-line health facilities. In this paper, we examine the current state of the art in CV as applied to the medical domain. We discuss the main challenges in CV and intelligent data-driven medical applications and suggest future directions to accelerate research, development, and deployment of CV applications in health practices. First, we critically review existing literature in the CV domain that addresses complex vision tasks, including: medical image classification; shape and object recognition from images; and medical segmentation. Second, we present an in-depth discussion of the various challenges that are considered barriers to accelerating research, development, and deployment of intelligent CV methods in real-life medical applications and hospitals. Finally, we conclude by discussing future directions.

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Evolutionary improved object detector for ultrasound images

Cited by 14 publications

References 13 publications

Real-time face tracking in video content using Viola-Jones algorithm

Real-time face tracking in video content using Viola-Jones algorithm

Performance analysis of a surveillance system to detect and track vehicles using Haar cascaded classifiers and optical flow method

Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward

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