Current research opportunities of image processing and computer vision

Abstract

Image processing and computer vision is an important and essential area in today’s scenario. Several problems can be solved through computer vision techniques. There are a large number of challenges and opportunities which require skills in the field of computer vision to address them. Computer vision applications cover each band of the electromagnetic spectrum and there are numerous applications in every band. This article is targeted to the research students, scholars and researchers who are interested to solve the problems in the field of image processing and computer vision. It addresses the opportunities and current trends of computer vision applications in all emerging domains. The research needs are identified through available literature survey and classified in the corresponding domains. The possible exemplary images are collected from the different repositories available for research and shown in this paper. The opportunities mentioned in this paper are explained through the images so that a naive researcher can understand it well before proceeding to solve the corresponding problems. The databases mentioned in this article could be useful for researchers who are interested in further solving the problem. The motivation of the article is to expose the current opportunities in the field of image processing and computer vision along with corresponding repositories. Interested researchers who are working in the field can choose a problem through this article and can get the experimental images through the cited references for working further.

An AI-enabled pre-trained model-based Covid detection model using chest X-ray images

“…After the diagnosis of the first Covid case in 2019, several Deep Learning and Machine Learning based approaches like ChexNet [26], ChestNet [31], have been proposed to detect Covid-19. Image segmentation [9,22] can also be used for identifying the location and severity of the Covid. Most of the AI-based approaches used for the Covid detection use the pre-trained model because the publicly available dataset for the research number is small in size.…”

“…This paper shown the comparative analysis of four different pre-trained model for Covid detection. Based on the result shown in Tables 8,9,10,1,12,13,14,15,16,17,18,and 19 and Figs. 10,11,12,13,14,15 and 16, it can be concluded that the InceptionResnetV2 model performs well as compare to the other pre-trained model.…”

HCIU: Hybrid clustered inception‐based UNET for the automatic segmentation of organs at risk in thoracic computed tomography images

“…It is used for semantic segmentation followed by instance segmentation. Later various extensions in the UNET model have been used to enhance its ability and solve several challenges in medical image segmentation 16,17 . In 2019, SegTHOR international competition was held on the topic “Automatic Segmentation of Organs at risk in Thoracic CT images.” Trullo et al, 18 the competition organizer, proposed a deep learning‐based technique for thoracic OAR segmentation.…”

Expression Recognition Using Improved AlexNet Network in Robot Intelligent Interactive System

“…With the development of deep learning, more and more researchers pay attention to this hot field [20]. Facial expression recognition integrates many technologies such as machine learning, pattern recognition, and computer vision.…”