Envision: Intelligent, Reliable, Quality Solution

1. Envision: Intelligent, Reliable, Quality Solution Mausumi Acharyya, Ph.D. CEO Advenio TecnoSys (P) Ltd

2. Executive Summary

3. Our Offering Image Analytics Video Analytics Big Data Analytics Forensic Analysis HPC • Image Forensic Applications: • Image & Video Analysis - Examination, evaluation, analysis, enhancement, authentication, comparison • Image & Video Authentication – validate authenticity • Comparative Analysis - comparisons of people, clothing, or vehicles involved in crimes or accidents, or other objects of evidence High Performance Computing Services: Design, Develop & Maintain Applications for large data set computation in real time using immense parallel processing capabilities of CPU/GPU, GPGPU • Image Analysis Applications : • Healthcare – Medical Images (CT, MRI, PET, X-ray etc.), microscopic images (histology, cytology) , molecular images (gene expression, microarray) data • Life Science – Bioinformatics, Biotechnology • Security – Biometrics (face, finger print, iris recognition) • Industrial Imaging – Defect Identification • Defense – Radar Images • Security Proactive Solutions: • Number plate recognition • Occupancy detection • Intelligent scene verification • People counting • Perimeter protection • Camera tampering alarm • Traffic flow monitoring • Panic alarm • Left object detection • ML for Big Data: • Assessment of statistical • methodology needs/ • possibilities • Custom ML modeling and • algorithm design • Scalability planning • Implementation • architecture and • integration Image Processing & Vision Security Machine Learning Image Forensic Parallel Processing

4. Research & Development Innovative Solution Research & Development Original algorithm development as per market need Modification of existing or published solutions We identify the specific cutting-edge technologies and need in healthcare domain and design and develop innovative solutions based on these needs Advenio Upgradation Consultation Technical Consultation Product development consultation We offer upgradation of existing products in absence of right resources and expertise at client’s end We provide a wide range of solutions and services that help organizations to transform their business Productization Convert research prototype to deliverable product We offer complete productization of research output at academic level and go for licensing

5. Knowledge Base

6. Specialized Knowledge • Object Recognition & Detection • Shape Analysis • Segmentation • Texture Analysis & Synthesis • Image Reconstruction • Image & Video matching • Image Compression & Decompression • Feature extraction in spatial and frequency domain • Data Fusion/Registration • Pre- and Post- Processing (image corrections, noise removal, deblurring, image enhancement etc.) • Classification and Prediction • Video Processing

7. Domain Healthcare – Medical Images (CT, MRI, PET, X-ray etc.), microscopic images (histology, cytology) , molecular images (gene expression, micro-array) data Life Science – Bioinformatics, Biotechnology Security – Biometrics (face, finger print, iris recognition) Industrial Imaging – Defect/Purity Identification (Textile, Food, Consumable Items, Civil Structure, Mechanical Systems, Steel Plant, Coal Mines and many more) Video Processing - Number plate recognition, Occupancy detection, Intelligent scene verification, People counting, Left object detection, Camera tampering alarm, Traffic flow monitoring etc. Defense – Radar Images Agriculture – Satellite Images Mining - Satellite Images Climatology - Satellite Images Social & Media – Any kind of Image Processing for Fun Applications And Many More

8. Case Studies Credible Projects

9. Texture Analysis • Considerable knowledge and experience on Texture Analysis • Developed several novel algorithms for Texture Analysis • Segmentation of multi-textured images • Textures which are even difficult to discriminate visually by human eye were being discriminated by the machine vision algorithm developed • Features developed were affine transformation (scale, rotation, translation) invariant • Document image (scanned documents) segmentation for separating textual and graphics parts applicable for second generation compression • Features developed were invariant to skewness, resolution, rotation etc. • Satellite image segmentation for classifying different regions like: habitation, vegetation, water bodies, man-made structures, open areas etc. • Designed and developed a novel neuro-fuzzy based unsupervised classifier for this purpose

10. Texture Analysis Algorithm involves in-depth knowledge of Texture Analysis, Wavelet Analysis, Feature Extraction, Classification, Fuzzy Set Theory, Neural Network & Soft Computing Input Textured image where some of the regions are not discriminable as different class even visually Segmented image based on different textured regions Input Textured image where some of the regions are not discriminable as different class even visually Segmented image based on different textured regions Novelty of the algorithm is that it identifies textured regions as different class which are even very difficult to identify visually by human

11. Document Segmentation – Second Generation Compression Skewed image and its segmented output Test image with document skewed and text regions with different orientations and its segmented output Test image with non-convex and overlapping object boundaries and its segmented output Novel algorithm developed for segmentation of textual part from graphics part which is essential for second generation compression. Here text and graphics parts were considered as two different textured regions.

12. Satellite Image Classification Several regions were accurately segmented by the algorithm based on textures. In the Bombay IRS image even the two different densities in the Arabian Sea were identified correctly. In the Calcutta IRS image the open space which is a race course and even the Howrah bridge were identified correctly.

13. Nodule (Lesion) Detection in Chest X-ray 4 US Patents Novel algorithms were developed for identification of nodules (lesions) in chest X-rays. Chest X-ray data is a 2D projection image where each pixel represents a volumetric integration posing a challenge in detection and estimation of nodules and their characteristics. Several algorithms were developed to reduce False Positives or Nodule-look-alikes detection. Algorithm involves in-depth knowledge of Segmentation, Mathematical modeling, Pre- & Post Processing, Fractal Analysis, Shape Analysis, Image Analysis, Machine Learning, Statistical Analysis

14. Bleed (Aneurysm) Detection in Brain CT, Trauma Cases 2 US Patents Novel algorithms were developed for identification of subtle bleeds in brain CT images without contrast for trauma cases posing immense challenge Several algorithms were developed to reduce False Positives bleed-look-alikes(calcification, fresh-flowing blood, bright falx) Algorithm involves in-depth knowledge of Segmentation, Registration, Mathematical modeling, Pre- & Post Processing, Morphological Operations, Image Analysis, Machine Learning

15. Lie Detection in Functional MRI (fMRI) Images Novel approach one of the first attempts to find alternative to Polygraphs. Novel algorithm for identifying whether someone is telling a lie or truth based on functional MRI images. A one hundred percent classification accuracy was obtained on a set of unknown data (images) Algorithm involves exhaustive use of Registration both Rigid & Deformable and Non-linear Pattern Classification

16. Tuberculosis Bacilli Detection in Sputum Smears (microscopic image) US Patent Algorithm identifies TB Bacilli in microscopic images of sputum smears Algorithm based on Color Image analysis, Morphology, Machine Learning

17. Hairline Crack Detection in Bone X-ray, CT etc US Patent Algorithm involves use of exhaustiveImage analysis like several feature extraction including fractal analysis, Gabor orientation mapping etc. & Machine Learning Techniques

18. Foreign Material and Crack Detection in Chocolate Bars (X-ray) Original image Crack identification Original image Identified foreign element Defect Analysis in X-ray images of Chocolate bars This involved an unsupervised technique to identify crack or presence of any foreign materials inside the bars. In this analysis no reference image were used and it is completely a machine vision technique Original image Identified foreign element

19. Segmentation of stained microscopic image of Root Segmentation of stained microscopic images of Root Algorithm involves different state-of-art image segmentation techniques

20. Pulmonary Embolism Detection in CT Angiogram Pulmonary embolism (PE) is a serious medical condition, characterized by the partial/complete blockage of an artery within the lungs Novel algorithm developed for PE detection and several algorithms for reducing False Positives or PE-look-alikes Algorithm involves use of exhaustive Image analysis & Machine Learning Techniques

21. Subtle Nodule Detection in Low Resolution Lung CT images Nodule Algorithm identified very subtle nodules which were missed by radiologists Algorithm involves use of exhaustive Image analysis, Deformable Registration & Machine Learning Techniques

22. Alzheimer Detection in Diffusion Tensor MRI (DTMRI) Images Diffusion tensor tractography Algorithm based on Singular Value Decomposition, Tensor Analysis, Deformable Registration andintensive Mathematical modeling

23. Mammogram Segmentation and Nodule Detection Mammogram segmentation and Nodule detection. It is extremely challenging to segment mammograms which are digitized from X-ray films due to presence of noise and other artifacts Algorithm based on Morphological operations, Segmentation based on Active Contour and Fuzzy Sets and intensive Mathematical modeling

24. Bitting Code Generation in Locksmith Key Locksmith Key Coding: Mobile Application Automatic detection, segmentation, bit edge profiling and generation of code from space and depth information

25. Face Authentication Face Authentication: Face recognition feature extraction, authentication

26. Iris Authentication Iris Authentication: Eye lash and other denoising and segmentation of pupil and iris region. Encoding the iris for authentication

27. Optical Character Recognition (OCR) Automated Answer Script Evaluation (Optical Character Recognition) Algorithm involves rigid registration and Scale Invariant Feature Transform (SIFT)

28. Optical Character Recognition Removal of “Phrase” from Text Document

29. Bioacoustics Bird Chirp Identification and Classification

30. Accelerometer Data Analysis Golf Swing Key Points Identification

31. Watermark Watermarking - novel algorithm developed to embed patient information in medical images as watermark The uniqueness and novelty of the algorithm lies in the fact that apart from the use of embedded watermark as an information source we can watermark some extra ‘text’ information pertaining to the image. We see this as a revolutionary tool in the arsenal of a radiologist using a CAD suite, wherein he can embed certain crucial information into an image rather than relying on the DICOM header. The significant benefit would be the selective access of this information and its being free of traditional viewing platforms. Thus the watermark here acts in actual way of both conveying information as well as providing security. A failure of the watermark would mean the non-reliability of both the image as well as the additional information thereby maintaining its traditional purpose. Algorithm involves Wavelet Analysis, quantization, coding Published Patent

32. Satellite Image Segmentation Region classification of satellite images into different categories like vegetation, building area, shadows, road area etc

33. Satellite Image Segmentation

34. Satellite Image Segmentation

35. Liver Histology (Biopsy) Image Analysis for Automatic Detection and Grading of Liver Diseases Automatic Lesion detection and gradation of Liver diseases Algorithm involves novel machine learning and image processing techniques for extraction of features and classification Steatosis Lobular Inflammation

36. Histology (Microscopic Tissue Images) Image Analysis of different Organs for aiding Drug Development Detection of Normal and Abnormal Organs Algorithm involves novel machine learning and image processing techniques for extraction of features and classification

37. Image Forensic Identifying image tampering, alteration or forgery Passive Authentication - Patterns of original images are distinguishable due to the different imaging devices and image processing inside them. Original patterns constrained by the statistical characteristics in natural scenes, physical conditions in a scene, etc. would be altered after tampering. • Passive forensics can be converted to a problem of pattern recognition • Solution to the problem is finding the different patterns according to the knowledge from various imaging devices or the manipulations or the natural scene constraints, etc. • Selected patterns with distinguishing ability are crucial for this new technology

38. Passive Forensic Image X Compare Knowledge of image acquisition model Similarities between patterns and characteristic features measured. Confidence measure for each imaging device to identify the source of the image is computed. Imaging Device • Identification of image source • Imaging devices have varying characteristics due to different • physics apparatus • image processing • parameters applied inside the imaging devices • Lead to different patterns of the output images • Use these patterns as inherent “fingerprints” of the imaging devices to identify the source of the image

39. Passive Forensic Image X Compare Knowledge of image manipulation model Extract features from image X and obtain the original/ altered patterns mainly using the knowledge of the image manipulation model. Compare the distance between the features and the patterns to decide whether or not image X has been altered Original/ Altered Image • Detection of image alteration • Original images always contain some consistent characteristics • noise distribution • light condition • Characteristics change after image post-processing (alterations) • Some features of the altered images become more or less inconsistent • Finding the differences before and after the operations is the key of the technology

40. Image Forensic Fourier analysis of histograms of the images to determine if a JPEG image underwent double compression Localize which portions underwent double compression by analyzing difference images Any forgery in the image or splicing of two images from different cameras can be identified by analyzing the correlations introduced by performing color filter array (CFA) interpolation and demosaicking Any tampering can be measured by the local correlation of camera noise or photo-response non-uniformity noise (PRNU) and the image Forgery due to splicing of images require resampling which disturbs the specific correlation of the image. Estimating this correlation using expectation maximization can identify the forgery A common manipulation is to copy and paste portions of an image to replicate an object or conceal a person in a scene called cloning. Presence of identical (or virtually identical) regions in an image can, therefore, be used as evidence of tampering. Image similarity measure, by matching key points in the images using different techniques like scale invariant feature transform (SIFT) and random sample consensus algorithm (RANSAC) can be used to identify this cloning

41. Image Forensic Computer graphics (CG) capable of generating highly realistic images. But CG images are rendered under idealized models of geometry, lighting, camera optics and sensors, and their underlying statistics differ from those of photographic images. Image decomposition at different orientation, scale and spatial frequency that are localized in spatial position would capture all the statistical irregularities in case of CG images Creating a photo composite requires translation, scaling, rotations of portions of an image. Such image-based manipulations can change the effective intrinsic camera parameters. Differences in these estimated parameters can be used as evidence of tampering Shadow analysis (light travels in straight line so lines drawn on shadows and objects should intersect at one point (light source). This can be used to analyze any forgery Image created by splicing together individual images is difficult to exactly match the lighting effects due to directional lighting (e.g., the sun on a clear day). Differences in lighting can be a telltale sign of tampering. Direction of the light source can be estimated for different objects/people in an image, inconsistencies in the lighting direction can be used as evidence of tampering

42. Products OptiNio – Retinal abnormality detection software CheckCount– Automated counter of production of any item

43. Brief Profile of Founder & CEO Dr. Mausumi Acharyya • Post-Doc (Medical Imaging), University of Pennsylvania, USA • PhD, Computer Science (Image Processing), Indian Statistical Institute, India • M.Tech and B.Tech (Electronics & Telecommunication), Calcutta University, India • 13+ years in IT industry (GE Global Research, Siemens, Defense Research & Development Organization) • 20+ years of rich research experience in Multifarious domains • Distinguished research and development exposure in • Signal/Image processing • Medical Image Processing • Machine Learning and Vision • In-depth understanding and extensive knowledge of designing and development of Image, Video, Data analytics applications • Key in successfully delivering several commercial products during her engagement with the above organizations • Mausumi holds several US Patents and international publications to her credit

44. Contacts

45. Thank You

46. Thank You Transpiring Innovation