Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

تعد مجالات الصورة وعلاماتها الحركية حضوراً دلالياً للاتصال العلامي واتساعاً في الرابطة الجدلية ما بين الدوال ومداليها، التي تقوم بها الرؤية الاخراجية لإنتاج دلالات اخفائية تمتلك جوهرها الانتقالي عبر الافكار بوصفها معطيات العرض، ويسعى التشفير الصوري الى بث ثنائية المعنى داخل الحقول المتعددة للعرض المسرحي، ولفهم المعنى المنبثق من هذه التشفيرات البصرية، تولدت الحاجة لبحث تشكيل هذه التشفيرات وكيفية تح

In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and

Many image processing and machine learning applications require sufficient image feature selection and representation. This can be achieved by imitating human ability to process visual information. One such ability is that human eyes are much more sensitive to changes in the intensity (luminance) than the color information. In this paper, we present how to exploit luminance information, organized in a pyramid structure, to transfer properties between two images. Two applications are presented to demonstrate the results of using luminance channel in the similarity metric of two images. These are image generation; where a target image is to be generated from a source one, and image colorization; where color information is to be browsed from o

The study discusses the marketing profile of electoral candidates and politicians especially the image that takes root in the minds of voters has become more important than the ideologies in the technological era or their party affiliations and voters are no longer paying attention to the concepts of a liberal, conservative, right-wing or secular, etc. while their interests have increased towards candidates. The consultants and image experts are able to make a dramatic shift in their electoral roles. They, as specialists in the electoral arena, dominate the roles of political parties.
The importance of the study comes from the fact that the image exceeds its normal framework in our contemporary world to become political and cultural

With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases