Depth of field simulation for still digital images using a 3D camera

In a world where digital photography is almost ubiquitous, the size of image capturing devices and their lenses limit their capabilities to achieve shallower depths of field for aesthetic purposes. This work proposes a novel approach to simulate this effect using the color and depth images from a 3D camera. Comparative tests yielded results similar to those of a regular lens.

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Accurate Instance-Based Segmentation for Boundary Detection in Robot Grasping Application

Applied Sciences ◽

10.3390/app11094248 ◽

2021 ◽

Vol 11 (9) ◽

pp. 4248

Author(s):

Hong Hai Hoang ◽

Bao Long Tran

Keyword(s):

Object Segmentation ◽

State Of The Art ◽

Rapid Development ◽

Spatial Relationship ◽

Learning Technologies ◽

Average Precision ◽

Novel Approach ◽

3D Camera ◽

Robot Grasping ◽

Instance Segmentation

With the rapid development of cameras and deep learning technologies, computer vision tasks such as object detection, object segmentation and object tracking are being widely applied in many fields of life. For robot grasping tasks, object segmentation aims to classify and localize objects, which helps robots to be able to pick objects accurately. The state-of-the-art instance segmentation network framework, Mask Region-Convolution Neural Network (Mask R-CNN), does not always perform an excellent accurate segmentation at the edge or border of objects. The approach using 3D camera, however, is able to extract the entire (foreground) objects easily but can be difficult or require a large amount of computation effort to classify it. We propose a novel approach, in which we combine Mask R-CNN with 3D algorithms by adding a 3D process branch for instance segmentation. Both outcomes of two branches are contemporaneously used to classify the pixels at the edge objects by dealing with the spatial relationship between edge region and mask region. We analyze the effectiveness of the method by testing with harsh cases of object positions, for example, objects are closed, overlapped or obscured by each other to focus on edge and border segmentation. Our proposed method is about 4 to 7% higher and more stable in IoU (intersection of union). This leads to a reach of 46% of mAP (mean Average Precision), which is a higher accuracy than its counterpart. The feasibility experiment shows that our method could be a remarkable promoting for the research of the grasping robot.

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Dramaturgia fotografii. Między teorią a osobistym doświadczeniem (przypadek Rolanda Barthes’a)

Przestrzenie Teorii ◽

10.14746/pt.2021.36.5 ◽

2021 ◽

pp. 91-105

Author(s):

Irena Górska

Keyword(s):

Digital Images ◽

Digital Photography ◽

Roland Barthes ◽

The Spectator

The article discusses Roland Barthes’ experience of photography and presents its distinctive dramaturgy, which emerges from the reflections of the author of The Light of Image. It is played out between attempts at a theoretical grasp of the essence of photography and a personal, intimate experience of being photographed, but also of being a spectator looking at various photographs. Barthes places this experience in two basic perspectives. The first is connected with the process of taking photographs and the second with the experience of the spectator. This also includes the experience of photography with one’s own image, which according to the author, is always an experience of oneself as someone else, and the experience of searching for “the truth of photography”, especially important in the context of the photographs of his deceased mother. It is significant in Barthes’s concept that he is talking about traditional photography which had a completely different character and performed different functions to digital images do today. Moreover, as the author notes, Barthes’s theoretical findings would be untenable in relation to digital photography.

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Images on the Move

10.14361/9783839452462 ◽

2021 ◽

Keyword(s):

Social Media ◽

Streaming Media ◽

Digital Images ◽

Digital Photography ◽

Contemporary Society

In contemporary society, digital images have become increasingly mobile. They are networked, shared on social media, and circulated across small and portable screens. Accordingly, the discourses of spreadability and circulation have come to supersede the focus on production, indexicality, and manipulability, which had dominated early conceptions of digital photography and film. However, the mobility of images is neither technologically nor conceptually limited to the realm of the digital. The edited volume re-examines the historical, aesthetical, and theoretical relevance of image mobility. The contributors provide a materialist account of images on the move - ranging from wired photography to postcards to streaming media.

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Adaptive Median Filtering Based on Unsupervised Classification of Pixels

Handbook of Research on Computational Intelligence for Engineering, Science, and Business ◽

10.4018/978-1-4666-2518-1.ch011 ◽

2013 ◽

pp. 273-296 ◽

Cited By ~ 2

Author(s):

J. K. Mandal ◽

Somnath Mukhopadhyay

Keyword(s):

Clustering Algorithm ◽

Digital Images ◽

Unsupervised Classification ◽

Median Filtering ◽

Adaptive Window ◽

Novel Approach ◽

Weighted Median ◽

Window Selection ◽

Filtering Approach

This chapter deals with a novel approach which aims at detection and filtering of impulses in digital images through unsupervised classification of pixels. This approach coagulates directional weighted median filtering with unsupervised pixel classification based adaptive window selection toward detection and filtering of impulses in digital images. K-means based clustering algorithm has been utilized to detect the noisy pixels based adaptive window selection to restore the impulses. Adaptive median filtering approach has been proposed to obtain best possible restoration results. Results demonstrating the effectiveness of the proposed technique are provided for numeric intensity values described in terms of feature vectors. Various benchmark digital images are used to show the restoration results in terms of PSNR (dB) and visual effects which conform better restoration of images through proposed technique.

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Nonparametric background modelling and segmentation to detect micro air vehicles using RGB-D sensor

International Journal of Micro Air Vehicles ◽

10.1177/1756829318822327 ◽

2019 ◽

Vol 11 ◽

pp. 175682931882232

Author(s):

Navid Dorudian ◽

Stanislao Lauria ◽

Stephen Swift

Keyword(s):

Background Subtraction ◽

High Speed ◽

Micro Air Vehicles ◽

Background Model ◽

Depth Information ◽

Subtraction Technique ◽

Depth Images ◽

Novel Approach ◽

Model Update ◽

Air Vehicles

A novel approach to detect micro air vehicles in GPS-denied environments using an external RGB-D sensor is presented. The nonparametric background subtraction technique incorporating several innovative mechanisms allows the detection of high-speed moving micro air vehicles by combining colour and depth information. The proposed method stores several colour and depth images as models and then compares each pixel from a frame with the stored models to classify the pixel as background or foreground. To adapt to scene changes, once a pixel is classified as background, the system updates the model by finding and substituting the closest pixel to the camera with the current pixel. The background model update presented uses different criteria from existing methods. Additionally, a blind update model is added to adapt to background sudden changes. The proposed architecture is compared with existing techniques using two different micro air vehicles and publicly available datasets. Results showing some improvements over existing methods are discussed.

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A Novel Robust Approach for Computing DE-9IM Matrices Based on Space Partition and Integer Coordinates

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10110715 ◽

2021 ◽

Vol 10 (11) ◽

pp. 715

Author(s):

Enrico Romanschek ◽

Christian Clemen ◽

Wolfgang Huhnt

Keyword(s):

Geometric Features ◽

Spatial Relationships ◽

Two Dimensional ◽

Robust Approach ◽

Comparative Tests ◽

Spatial Decomposition ◽

Space Partition ◽

Novel Approach ◽

Novel Method ◽

Robust Computation

A novel approach for a robust computation of positional relations of two-dimensional geometric features is presented which guarantees reliable results, provided that the initial data is valid. The method is based on the use of integer coordinates and a method to generate a complete, gap-less and non-overlapping spatial decomposition. The spatial relationships of two geometric features are then represented using DE-9IM matrices. These allow the spatial relationships to be represented compactly. The DE-9IM matrices are based on the spatial decomposition using explicit neighborhood relations. No further geometric calculations are required for their computation. Based on comparative tests, it could be proven that this approach, up to a predictable limit, provides correct results and thus offers advantages over classical methods for the calculation of spatial relationships. This novel method can be used in all fields, especially where guaranteed reliable results are required.

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A Novel Approach to Vehicle Number Identification using Raspberry pi 3

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit1952346 ◽

2019 ◽

pp. 64-67

Author(s):

N. Varshini ◽

Sumedha Kasarla ◽

Shaik Subhani

Keyword(s):

Real Time ◽

Traffic Signals ◽

Raspberry Pi ◽

Identification System ◽

License Plate ◽

Text Format ◽

Novel Approach ◽

Image Conversion ◽

Image Capturing ◽

Conversion Technology

Vehicle Number Identification using Raspberry pi 3 is an image conversion technology which captures the license plate of a vehicle. The main aim is to make an effective and accurate license number plate identification system. This system is carried out and performed in the areas where traffic signals are present and the camera is placed on the signal which is connected to raspberry pi and it sends signals to the server and it can also be used in apartments or residencies for capturing all the vehicle numbers entering the building. This system at first detects the vehicle license plate and then captures it .It then converts the image into the text. The text of the license plate is displayed on the screen using the image conversion. Open CV and OCR are the two software's used for image capturing and conversion of that into text format respectively. The resulting data is then displayed on the screen and saved into a folder. The whole system is developed on Raspberry Pi desktop and its performance is used in real-time. It is observed from this experiment that the system mainly detects and captures the vehicle license plate, converts the image into text and displays it on the screen successfully.

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A Novel Approach of Restoration of Digital Images Degraded by Impulse Noise

International Journal of Computer Vision and Image Processing ◽

10.4018/ijcvip.2014040101 ◽

2014 ◽

Vol 4 (2) ◽

pp. 1-17 ◽

Cited By ~ 1

Author(s):

Rashmi Kumari ◽

Anupriya Asthana ◽

Vikas Kumar

Keyword(s):

Impulse Noise ◽

Fuzzy Inference ◽

Digital Images ◽

Window Size ◽

Qualitative And Quantitative Analysis ◽

Inference System ◽

Qualitative And Quantitative ◽

Novel Approach ◽

Neuro Fuzzy ◽

Restoration Method

Restoration of digital images degraded by impulse noise is still a challenge for researchers. Various methods proposed in the literature suffer from common drawbacks: such as introduction of artifacts and blurring of the images. A novel idea is proposed in this paper where presence of impulsive pixels are detected by ANFIS (Adaptive Neuro-Fuzzy Inference System) and mean of the median of suitable window size of noisy image is taken for the removal of the detected corrupted pixels. Experimental results show the effectiveness of the proposed restoration method both by qualitative and quantitative analysis.

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