Towards Effective Image Forensics via A Novel Computationally Efficient Framework and A New Image Splice Dataset

Splice detection models are the need of the hour since splice manipulations can be used to mislead, spread rumors and create disharmony in society. However, there is a severe lack of image splicing datasets, which restricts the capabilities of deep learning models to extract discriminative features without overfitting. This manuscript presents two-fold contributions toward splice detection. Firstly, a novel splice detection dataset is proposed having two variants. The two variants include spliced samples generated from code and through manual editing. Spliced images in both variants have corresponding binary masks to aid localization approaches. Secondly, a novel Spatio-Compression Lightweight Splice Detection Framework is proposed for accurate splice detection with minimum computational cost. The proposed dual-branch framework extracts discriminative spatial features from a lightweight spatial branch. It uses original resolution compression data to extract double compression artifacts from the second branch, thereby making it 'information preserving.' Several CNNs are tested in combination with the proposed framework on a composite dataset of images from the proposed dataset and the CASIA v2.0 dataset. The best model accuracy of 0.9382 is achieved and compared with similar state-of-the-art methods, demonstrating the superiority of the proposed framework

A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler

Image splice manipulation presents a severe challenge in today's society. With easy access to image manipulation tools, it is easier than ever to modify images that can mislead individuals, organizations or society. In this work, a novel, "Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler" has been proposed. It contains a unique "visually attentive multi-domain feature extractor" (VA-MDFE) that extracts attentional features from the RGB, edge and depth domains. Next, a "visually attentive downsampler" (VA-DS) is responsible for fusing and downsampling the multi-domain features. Finally, a novel "visually attentive multi-receptive field upsampler" (VA-MRFU) module employs multiple receptive field-based convolutions to upsample attentional features by focussing on different information scales. Experimental results conducted on the public benchmark dataset CASIA v2.0 prove the potency of the proposed model. It comfortably beats the existing state-of-the-arts by achieving an IoU score of 0.851, pixel F1 score of 0.9195 and pixel AUC score of 0.8989

Datasets, Clues and State-of-the-Arts for Multimedia Forensics: An Extensive Review

With the large chunks of social media data being created daily and the parallel rise of realistic multimedia tampering methods, detecting and localising tampering in images and videos has become essential. This survey focusses on approaches for tampering detection in multimedia data using deep learning models. Specifically, it presents a detailed analysis of benchmark datasets for malicious manipulation detection that are publicly available. It also offers a comprehensive list of tampering clues and commonly used deep learning architectures. Next, it discusses the current state-of-the-art tampering detection methods, categorizing them into meaningful types such as deepfake detection methods, splice tampering detection methods, copy-move tampering detection methods, etc. and discussing their strengths and weaknesses. Top results achieved on benchmark datasets, comparison of deep learning approaches against traditional methods and critical insights from the recent tampering detection methods are also discussed. Lastly, the research gaps, future direction and conclusion are discussed to provide an in-depth understanding of the tampering detection research arena

A COMPARATIVE STUDY OF DRAINAGE OF BREAST ABSCESS BY CONVENTIONAL INCISION AND DRAINAGE VERSUS SUCTION DRAINAGE VERSUS ULTRASOUND-GUIDED NEEDLE ASPIRATION

Objectives: Breast abscesses are common among lactating women most prevalent in developing countries because of poor hygiene, malnutrition, and health conditions. In era of technical advances management of breast abscess has shifted to minimally invasive and painless techniques which are more patient friendly. This study compare outcomes in management of breast abscess by ultrasound-guided needle aspiration, suction drainage, and incision and drainage procedure. Methods: The present study was conducted in department of surgery in collaboration of MGM Medical College Indore with Government Medical College, Khandwa. A total 120 patients of breast abscess were divided in three groups. One group was managed by incision and drainage second group by suction drainage and third group by ultrasound-guided needle aspiration (40 patients in each group). Results: In our study, total 120 patients were analyzed, majority of the cases (40.8%) belong to 21–25 years age group. Post-operative pain, high recurrence rate, fistula formation, cessation of breast feeding, ugly scar formation, and longer duration of hospital stay were observed in incision and drainage procedure. Conclusions: USG-guided needle aspiration was the safest, cost effective, and widely accepted procedure in the treatment of breast abscess as compared to incision and drainage

RECENT ADVANCEMENTS IN EAR BIOMETRICS: A REVIEW

Ascertaining the identity of a person is quite an important aspect of Forensic Science. There are so many physiological features have been proved to be highly discriminating among individuals. Biometrics play a significant role in individualizing a person. Fingerprint, Palm print, Retina and Iris recognition are the most popular examples of it. Fingerprint and iris are generally considered to allow more accurate biometric recognition than the face, but the face is more easily used in surveillance scenarios where fingerprint and iris capture are not feasible. However, the face by itself is not yet as accurate and flexible as desired for this scenario due to expression changes, source of illumination, make-up, etc. Besides these limitations, ear images can be acquired in a similar manner to face images. A number of researchers have suggested that the human ear is unique enough to each individual to allow practical use as a biometric. In this article an attempt has been made to review all the recent researches of a decade made in the field of Ear Biometrics

Advances in Solid Dispersion Techniques for Enhancing Drug Solubility, Bioavailability and Controlled Release

Solid dispersion (SD) refers to the dispersion of active ingredients, whether one or more, within inert carriers in a solid state. This is achieved through methods like fusion, solvent, or solvent fusion. The solid dispersion technique is particularly valuable for enhancing the solubility of inadequately soluble drugs, particularly those falling under BCS Class II. This technique involves the utilization of carriers such as polyethylene glycol 4000, urea, and polyvinylpyrrolidone K 30 to improve the drug's solubility and dissolution properties. The method of solid dispersion has been utilized to improve the solubility, dissolution, and bioavailability of various natural drug components. Furthermore, solid dispersion has been investigated as a strategy for developing natural drug products with controlled or sustained release characteristics. The mechanism of action of this delivery system relies on the specific type of solid dispersion, as well as the interactions among the drugs, carriers, and other components incorporated into the formulation. Currently, there are various methods accessible for characterizing SDs, including X-ray diffraction, differential scanning calorimetry, FTIR spectroscopy, and dissolution testing, among others. The pharmaceutical uses of the Solid Dispersion technique encompass: augmenting drug absorption, achieving a uniform distribution of a small drug quantity in a solid state, and safeguarding unstable drugs by mitigating processes like hydrolysis, oxidation, and photooxidation

A Study of External Ear Morphological Variation in Central Indian Population for Genealogical Purposes

The study aims to determine the inheritance pattern of different morphological features of the external ear in three generations from five states of India to assess the similarities between P1, F1, and F2 generations. The research involved 62 families, each with 124 grandparents P1 (62 males and 62 females), 124 parents F1 (62 males and 62 females), and 82 F2 generations (53 males and 29 females), a total of 330 samples, ranging in age from 1 to 75 years. All the samples were collected from five different states of India: Uttar Pradesh, Madhya Pradesh, Rajasthan, Bihar and Maharashtra. The external ear is distinct in terms of shape, size, and orientation. Its morphological variation aids in the determination of genetic inheritance. Fisher exact test was performed to assess the inter-generation association of morphological characteristics of the ear. Similar to other body characteristics, it is established that the auricle shape, lobule shape, and ear lobule attachment are also inherited. The associations of ear traits in three generations were studied, and the results might be used in forensic identification