Volume-4 Issue-3, April 2024 – Indian Journal of Image Processing and Recognition (IJIPR)

D102904040624

IJIPR Journal — Wed, 29 May 2024 10:29:34 +0000

The Indian Journal of Image Processing and Recognition (IJIPR) has ISSN 2582-8037 (online), open-access, peer-reviewed, periodical, bi-monthly international journal. This journal is published by Lattice Science Publication (LSP) in February, April, June, August, October and December. The aim of the journal is to publish high quality peer–reviewed original articles in the area of Image Processing and Recognition that covers Active Vision and Robotic Systems, Architecture of Imaging and Vision Systems, Autonomous Vehicles, Character and Handwritten Text Recognition, Chemical and Spectral Sensitization, Chemistry of Photosensitive Materials, Coating Technologies, Coding and Transmission, Cognitive Aspects of Image Understanding, Color Imaging, Communication of Visual Data, Data Fusion from Multiple Sensor Inputs, Display and Printing, Document Image Understanding, Generation and Display, Holography, Image Analysis and Interpretation, Image Capturing, Image Databases, Image Generation, Image Manipulation, Image Permanence, Image Processing, Image Processing Applications, Image Processing: Coding Analysis and Recognition, Image Representation, Image Sensing, Imaging Systems and Image Scanning, Implementation and Architectures, Latent Image, Materials for Electro-Photography, Monitoring and Surveillance, Network Architecture for Real-Time Video Transport, New Visual Services Over ATM/Packet Network, Non-Impact Printing Technologies, Object Modeling and Knowledge Acquisition, Photoconductors, Photographic Emulsions, Photopolymers, Prepress and Printing Technologies, Processing and Analysis, Protocols for Packet Video, Remote Image Sensing, Retrieval and Multimedia, Scene Modeling, Signal-Processing Aspects of Image Processing, Storage and Transmission, Video Coding Algorithms and Technologies for ATM/P. #Active Vision and Robotic Systems #Architecture of Imaging and Vision Systems #Autonomous Vehicles #Character and Handwritten Text Recognition #Chemical and Spectral Sensitization #Chemistry of Photosensitive Materials #Coating Technologies #Coding and Transmission #Cognitive Aspects of Image Understanding #Color Imaging #Communication of Visual Data #Data Fusion from Multiple Sensor Inputs #Display and Printing #Document Image Understanding #Generation and Display #Holography #Image Analysis and Interpretation #Image Capturing #Image Databases #Image Generation #Image Manipulation #Image Permanence #Image Processing #Image Processing Applications #Image Processing: Coding Analysis and Recognition #Image Representation #Image Sensing #Imaging Systems and Image Scanning #Implementation and Architectures #Latent Image #Materials for Electro-Photography #Monitoring and Surveillance #Network Architecture for Real-Time Video Transport #New Visual Services Over ATM/Packet Network #Non-Impact Printing Technologies #Object Modeling and Knowledge Acquisition #Photoconductors #Photographic Emulsions #Photopolymers #Prepress and Printing Technologies #Processing and Analysis #Protocols for Packet Video #Remote Image Sensing #Retrieval and Multimedia #Scene Modeling #Signal-Processing Aspects of Image Processing #Storage and Transmission #Video Coding Algorithms and Technologies for ATM/P #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLons

Comparison of Signal to Noise Ratio of Colored and Gray Scale Image in Clustered Condition from the Contours of the Images with the Help of Different Image Filtering Method
Abir Chakraborty
Abir Chakraborty, Department of Computer Science, Project Work Team Fellow, University of Coimbra.

Abstract: As we know the image can be processed with the help of different types of coding for example mat-lab. Here in this paper we are primarily focusing on some common filtering methodologies [5] related to image contour in clustered conditions. For filtering purpose in this paper we have used three different filtering technologies such as prewitt [3], sobel [3], canny [3] filtering. But on the other hand we have used both colored [1] and non-colored [3] images for clustering operations. Our main aim in this paper to show variations of signal to noise ratios for the colored and non-colored contour images with and without filtering. As per my request study the discussion of results very carefully to realize the deeper meaning of the journal [4].

Keywords: RGB, Lab, Gray, Contour, Prewitt, Sobel, Canny Filtering, Median, Coefficient Filtering.
Scope of the Article: Communication of Visual Data

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A804113010524

IJIPR Journal — Tue, 30 Apr 2024 06:11:13 +0000

An Overview of Text to Visual Generation Using GAN
Sibi Mathew
Sibi Mathew, MTech Scholar, Department of CSE TKM College of Engineering Kollam, Kerala, India.

Abstract: Text-to-visual generation was once a cumbersome task until the advent of deep learning networks. With the introduction of deep learning, both images and videos can now be generated from textual descriptions. Deep learning networks have revolutionized various fields, including computer vision and natural language processing, with the emergence of Generative Adversarial Networks (GANs). GANs have played a significant role in advancing these domains. A GAN typically comprises multiple deep networks combined with other machine learning techniques. In the context of text-to-visual generation, GANs have enabled the synthesis of images and videos based on textual input. This work aims to explore different variations of GANs for image and video synthesis and propose a general architecture for text-to-visual generation using GANs. Additionally, this study delves into the challenges associated with this task and discusses ongoing research and future prospects. By leveraging the power of deep learning networks and GANs, the process of generating visual content from text has become more accessible and efficient. This work will contribute to the understanding and advancement of text-to-visual generation, paving the way for numerous applica-tions across various industries.

Keywords: Computer Vision, Image Synthesis, Natural Lan- Guage Processing, Video Synthesis, Filler Images.
Scope of the Article: Communication of Visual Data

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