Object Detection and Recognition

Gollapudi, Sunila

doi:10.1007/978-1-4842-4261-2_5

Cited by 3 publications

(1 citation statement)

References 39 publications

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“…Despite considerable advances in computer vision, object detection is still an active topic of study [1][2][3][4]. This process is used in many fields, such as biomedical imaging, biometry, video surveillance, vehicle navigation, visual inspection, robot navigation, and remote sensing [1][2][3][4][5], to mention a few. Object identification has been considered an essential task and one of the biggest challenges in image processing [1][2][3][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Alternative Thresholding Technique for Image Segmentation Based on Cuckoo Search and Generalized Gaussians

et al. 2021

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Object segmentation is a widely studied topic in digital image processing, as to it can be used for countless applications in several fields. This process is traditionally achieved by computing an optimal threshold from the image intensity histogram. Several algorithms have been proposed to find this threshold based on different statistical principles. However, the results generated via these algorithms contradict one another due to the many variables that can disturb an image. An accepted strategy to achieve the optimal histogram threshold, to distinguish between the object and the background, is to estimate two data distributions and find their intersection. This work proposes a strategy based on the Cuckoo Search Algorithm (CSA) and the Generalized Gaussian (GG) distribution to assess the optimal threshold. To test this methodology, we carried out several experiments in synthetic and practical scenarios and compared our results against other well-known algorithms from the literature. These practical cases comprise a medical image database and our own generated database. The results in a simulated environment show an evident advantage of the proposed strategy against other algorithms. In a real environment, this ranks among the best algorithms, making it a reliable alternative.

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Section: Introductionmentioning

confidence: 99%

Alternative Thresholding Technique for Image Segmentation Based on Cuckoo Search and Generalized Gaussians

et al. 2021

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Virtual High Dynamic Range Imaging for Underwater Drone Navigation

Cyganek¹,

Woźniak

2018

Proceedings of the 6th IIAE International Conference on Industrial Application Engineering 2018

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Digital images contain few orders of magnitude smaller dynamic range than capabilities of a human eye. High dynamic range allows for perception of more details under wide lighting variations. Therefore acquisition of high dynamic range images is of high importance. However, the process of collecting of images at various exposures, then joining them together is not an easy one. Not always it is even possible to acquire a series of images of different exposures. However, even a single image due to not perfect conditions of acquisition usually contains much more information than available on the first sight. In this paper we show a method of so called virtual high dynamic range imaging formation which allows for obtaining at least virtually higher dynamical range just from an image acquired at a single exposure. Thanks to this the images convey more discriminative information as it is shown in the case of navigation of the underwater drone.

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Study Of Deep Learning Techniques For Differently Abled Applications And Detection Techniques

Anandh¹

2021

TURCOMAT

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In worldwide, Visually Impaired Persons (VIP) are facing several issue related to visual impairment and blindness and they are assisted with technical inventions. Based on the survey from World Health Organization (WHO), around 2.2 billion peoples are suffered from visual impairment and among them 1 million peoples are suffered by blindness. Vision is the major sensing organ of the human and to assist the VIP regarding this, there are various digital vision products are in the market which is based on digital technologies and advanced algorithms. This will transform the VIP’s vision world into audio to get to know about their surroundings includes objects, motion, obstacles and spatial locations. The objective of this paper is to provide the detailed survey about the existing object recognition, face recognition and text to voice recognition methods proposed to assist VIP. Due to the increase development of machine learning and deep learning algorithms, the digital image recognition and object recognition are become more efficient. These advanced technologies can make sure to assist the VIP to detect and recognize the people face and objects in front of them in the form of audio that are practiced by them on daily basis.

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Object Detection and Recognition

Cited by 3 publications

References 39 publications

Alternative Thresholding Technique for Image Segmentation Based on Cuckoo Search and Generalized Gaussians

Alternative Thresholding Technique for Image Segmentation Based on Cuckoo Search and Generalized Gaussians

Virtual High Dynamic Range Imaging for Underwater Drone Navigation

Study Of Deep Learning Techniques For Differently Abled Applications And Detection Techniques

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