Frequently Asked Questions

ImageProVision Technology is a leading global company in the physical testing space with an emphasis on Image Analytics. Our focus is on offering pioneering, customer-focused solutions and services to enhance the efficiency of our clients.

Image processing is a field of study that involves manipulating digital images using algorithms and techniques to enhance or extract useful information from the images. It encompasses tasks such as image enhancement, restoration, segmentation, and feature extraction.

Common image analysis techniques include:
Image segmentation: Dividing an image into meaningful regions or objects.
Object detection and recognition: Identifying and classifying objects within an image.
Image classification: Categorizing images into predefined classes or groups.
Feature extraction: Extracting relevant features or patterns from images for further analysis.
Image registration: Aligning multiple images for comparison or fusion.
Image restoration: Removing noise, blur, or other artifacts from degraded images.
Image compression: Reducing the size of an image while maintaining important information.
Morphological operations: Analyzing the shape and structure of objects within an image.

Image processing plays a crucial role in numerous fields, including medical imaging, surveillance, remote sensing, robotics, quality control, and computer vision. It enables the extraction of meaningful information, pattern recognition, and decision-making based on visual data.

Some common challenges in image processing include handling noise, variations in lighting conditions, occlusions, complex backgrounds, and dealing with large-scale datasets. Developing robust algorithms and techniques that are computationally efficient and applicable to diverse scenarios is an ongoing challenge.

While image processing focuses on manipulating and analyzing images to enhance or extract information, computer vision is a broader field that encompasses image processing but also involves higher-level understanding of images and videos. Computer vision aims to enable machines to interpret and understand visual information, such as object recognition, scene understanding, and image understanding in context.

Image processing techniques are widely used in medical imaging for tasks such as image enhancement, segmentation of anatomical structures, tumor detection, and quantitative analysis. It aids in diagnosis, treatment planning, and monitoring of various medical conditions, helping clinicians make informed decisions and improve patient care.

Yes, image processing can be applied to real-time applications with the use of efficient algorithms and hardware acceleration techniques. For example, real-time object tracking, surveillance systems, and autonomous vehicles utilize image processing techniques for immediate decision-making and response.

Ethical considerations in image processing include privacy concerns, ensuring data security, and maintaining the integrity of the processed images. It is important to handle personal or sensitive information in accordance with legal and ethical standards, especially in applications involving medical or surveillance data.

Image filters are used to modify the characteristics of an image. Some common types of filters include blur filters for smoothing, sharpening filters for enhancing edges, noise filters for reducing noise, and morphological filters for shape manipulation. Other filters include contrast enhancement filters, color manipulation filters, and edge detection filters.

Image segmentation involves dividing an image into distinct regions or objects based on their characteristics, such as color, texture, or intensity. Various algorithms, such as thresholding, region-based methods, and edge-based methods, are used to identify and separate different regions of interest in an image.

Image processing is essential for various tasks in autonomous vehicles, including object detection, lane detection, traffic sign recognition, and obstacle avoidance. By analyzing real-time video or image data from cameras mounted on the vehicle, image processing algorithms can provide valuable information to make informed decisions and ensure the safety of autonomous vehicles.

Image processing is widely used in quality control and inspection processes across industries. It helps identify defects, measure dimensions, assess product appearance, and detect anomalies in manufacturing or production lines. By automating these tasks, image processing improves efficiency, accuracy, and consistency in quality control processes.

Yes, image processing plays a critical role in facial recognition and biometric systems. It involves techniques such as face detection, feature extraction, and face matching to identify and verify individuals based on their facial characteristics. These applications find use in security systems, access control, and identity verification.

Image processing techniques are essential in AR and VR applications to overlay virtual objects on real-world scenes or create immersive virtual environments. Image processing helps with tasks such as camera tracking, image registration, object recognition, and depth estimation, enhancing the realism and interactivity of AR and VR experiences.

Image processing techniques may face limitations in cases where images have poor quality, significant noise, or complex scenes. Certain tasks, such as accurate 3D reconstruction or semantic understanding, may require additional data or specialized algorithms beyond traditional image processing techniques.

Image processing is instrumental in remote sensing and earth observation to extract valuable information from satellite or aerial imagery. It enables tasks such as land cover classification, vegetation analysis, change detection, and environmental monitoring, supporting various fields, including agriculture, forestry, urban planning, and disaster management.

Common image file formats include JPEG, PNG, TIFF, BMP, and GIF. Each format has its own characteristics, such as compression capabilities, color depth, and support for transparency, making them suitable for different use cases in image processing and storage

Image processing techniques play a vital role in medical diagnosis and treatment. They assist in tasks such as image registration for comparing medical scans, tumor segmentation for accurate measurements, image fusion for combining different imaging modalities, and image-guided interventions for precise surgical procedures.

Yes, image processing techniques can be extended to video processing. Video processing involves analyzing and manipulating consecutive frames of a video sequence. Tasks such as video stabilization, object tracking, motion estimation, and video compression utilize image processing algorithms applied to multiple frames.

Image processing techniques find applications in precision agriculture. They help assess crop health, detect diseases or pests, estimate vegetation indices, monitor growth patterns, and optimize irrigation and fertilization practices. By providing insights into plant health and growth, image processing aids in improving agricultural productivity.

Yes, image processing techniques are widely used in facial recognition systems and emotion analysis. Facial recognition involves identifying and verifying individuals based on facial features, while emotion analysis aims to detect and analyze facial expressions to infer emotions. These applications have implications in security, human-computer interaction, and psychological research.

Yes, image processing techniques are valuable in forensic investigations. They aid in tasks such as image enhancement for improving visibility, image super-resolution for recovering details, image comparison and matching for forensic analysis, and forgery detection for identifying tampered or manipulated images.

Image processing techniques have been embraced by artists and designers for creative expression. They enable various artistic transformations, filters, and effects that can be applied to images, photographs, or digital artwork to achieve unique visual styles, enhance aesthetics, and create captivating visual compositions.

Image processing techniques are instrumental in analyzing astronomical images captured by telescopes and spacecraft. They aid in tasks such as image stacking for noise reduction, image registration for aligning multiple images, and image enhancement to reveal faint details. Image processing enables astronomers to study celestial objects, analyze star clusters, detect galaxies, and explore the mysteries of the universe.

Image processing has significant applications in geology and remote sensing. It helps geologists analyze satellite or aerial images to identify geological formations, map land cover, detect changes in the Earth’s surface, and study environmental factors such as vegetation health, soil moisture, and geological hazards.

Image processing plays a crucial role in robotic perception and autonomous systems. It enables robots to analyze visual data from cameras or sensors, detect and track objects, navigate and map environments, and make informed decisions based on visual information. Image processing empowers robots to interact with their surroundings and perform tasks in various domains such as industrial automation, healthcare, and exploration.

Yes, image processing techniques are widely utilized in security and surveillance systems. They enable tasks such as motion detection, object recognition, people counting, and behavior analysis. By analyzing video or image streams, image processing algorithms enhance the effectiveness of security systems, enabling real-time monitoring, threat detection, and incident response.

Real-world image processing applications often face challenges such as varying lighting conditions, complex backgrounds, occlusions, and the need for real-time processing. These challenges require the development of robust algorithms, efficient computational methods, and the integration of machine learning techniques to handle diverse scenarios and ensure reliable performance.

Yes, image processing techniques are employed in virtual try-on applications in the fashion industry. They enable virtual fitting of clothes by mapping and overlaying garments onto a user’s body shape. Image processing algorithms can simulate how clothing items will look and fit, providing customers with a virtual try-on experience before making a purchase.

Image processing is vital for interpreting satellite and aerial images, particularly in applications such as land use mapping, urban planning, and environmental monitoring. It enables the extraction of meaningful information from these images, such as identifying infrastructure, tracking land cover changes, monitoring deforestation, and assessing environmental impacts.

Image processing is extensively used in biomedicine and medical imaging research. It aids in tasks such as image reconstruction, image fusion, tumor segmentation, blood vessel analysis, and quantitative analysis of medical images. These techniques support medical research, clinical diagnosis, treatment planning, and monitoring of diseases and conditions.

Yes, image processing techniques are applied in content-based image retrieval systems. They enable the extraction of relevant features from images, such as color, texture, and shape, to build indexes and facilitate efficient retrieval of similar images from large image databases based on their visual content.

Image processing techniques have significant applications in archaeology and cultural heritage preservation. They aid in tasks such as image restoration and enhancement of deteriorated or damaged artworks, 3D reconstruction of archaeological sites, analysis of ancient manuscripts, and documentation of cultural artifacts to preserve and study our shared heritage.

Particle size analysis can be done by various methods. However, the two below methods are the most popular:
Laser Diffraction Technique
Microscopy Technique
In the Laser Diffraction Technique, it gives the information of Particle only basis of their size (No difference between the single particles and the agglomeration). That’s because of its diffraction technique the laser falls on the particle where it has created a certain angle and provides the image of a particle through the detector on the system, where the agglomerates are considered as bigger particles and the single particles are considered as small particle according to its size distribution range). It converts an equivalent sphere. The value of size distribution will provide only the basis of volumetric SED.
In the Microscopic Technique, it is only a direct method technique where transparency is available and every particle is visible, hence the analysis can be done not only on the basis of size but also on the basis of shape. Hence, we are getting the complete morphological details, such as the Intensity of light on particles, Convexity, Solidity, Aspect ratio, Length and Width etc.
In ImageProVision applications or software provides detailed information about particle based on their: Length, Width, Aspect ratio, Intensity of light on particles, Convexity, Solidity, CED (Circular equivalent diameter) also based on Volumetric SED (Spherical equivalent Diameter).
Since Microscopic Technology with IPV software is an image analysis technique, that has full transparency, because of the identification of single particles and agglomerates are easy to observe and differentiate, easy to get elongated particles, rectangular particles, API’s (Active Pharmaceutical Ingredient), globules etc. Therefore, you can trace every individual particle.

Manual analysis is time-consuming, and has chances to give errors while in manual observation or analysis, Human power is required for analysis.
Advanced particle size analysis technology is a unique and automated system that will reduce human error or manual error and get the complete report with accurate results and time efficiency. Also, less manpower will be used.

Yes, with ImageProVision’s software called ipvPClass (ipv Particle Classifier) we can easily classify API, Excipient, Globules, Agglomeration, and single particles with their different shape and size. The further various classification parameters available are based on Brightness, Image type, Shape, Size range, 5 Colors, Texture, and Sharpness. With these various parameter, we can easily classify API, Excipient, and Globules through Optical Microscopy.

Yes, our all-Microscopic ipv Softwares are 21 CFR part 11 compliant. In this, it follows all the rules and regulations to fulfil the need of 21 CFR part 11 compliant.

Our ipvPClass software has a unique algorithm through which the classification of crystalline, API, Cream, Gel, Suspension, Aerosol (DPI&MDI) and liquid samples are easy to observe.
Classifies isolated particles and agglomerations through the microscopic images and further classifies an isolated particle into API, excipient and globules with its uniquely made default Software parameters such as globules identification, enhance particles identification, and crystal identification these parameters will make the observation of sample so easy and time efficient.
Also, supportive software parameters such as Brightness, Image type, Shape, Size range, Color, Texture, and Sharpness will increase the chances to get the result accurately and classification of any kind of dosage form is possible and easy.
The sample prepared on a glass slide is kept under the microscope, images captured by the ipv camera attached to the microscope and the captured image is analyzed by the ipv software with its Patented and unique Algorithm. It classifies various particles in terms of API, excipient, and globules (For Crystalline particles by using polarized light on microscopy with ipv software parameter called Crystalline identification makes it more time efficient and easy to observe the crystal particles).

Microscopy analysis get recognition for particle based on size and shape, the need was to make it more productive and avoid the mistake done by individuals and it was required to make the microscopic analysis more advanced i.e., automatic movement. This is true for both particulate matter count as well as particle size analysis. In the Particulate matter counter, there is a need to analyse the filter paper to ensure that the entire filter paper is scanned automatically with the movement of X, Y, and Z movement. Hence, automatic movement is more accurate or preferred over the manual image-capturing method.

USP 788 & 789 is Standard US Pharmacopeia for USP 788 (Particulate Matter Counter in Injections) and USP 789 (Particulate Matter Counter in Ophthalmic Solutions).
It talks about two methods:
Light Obscuration Particle Count Test.
Microscopic Particle Count Test.
ImageProVision has two software which follow the method USP 788 i.e., ipvPCount and ipvAutoCount. Nowadays, Companies prefer to do microscopic test because it gives direct results. Also, it is more accurate.

Calibration and Validation is an important activity in Microscopy Particle size and shape Analysis. Calibration of the software is done by calibrating the Micrometer scale or slide called as Calibration slide. Calibration is important because we guide the software on how to convert pixels to micrometres and because of that, the sample images with particles will easily provide and identified its particles with accurate morphological details.
Validation is done by a certified predefined diameter of circles or predefined shapes; the Microscopic software system gives the result of certified predefined circles and shapes and then compared them with the actual size and shape. If it is within the acceptable limit, the software system is validated successfully.

Hot stage microscopy is an important method to study the changes in particle size and morphology of particles with respect to changes in temperature, most of the hot stage microscopy generates the images & the video but the analysis is done with the manual interpretation of the days’ images and the videos are done manually.
However, ImageProVision Technology PVT. Ltd. has given the solution to analyse variation in particle with hot stage microscopy, images and videos, ipvPHot generate a lot of statistics and graph on the changes in particle size, shape or morphological changes with respect to temperature and time.
In various research and quality purpose when particle classification is difficult to do based on imaging parameter then thermal Properties are used ipvPHot generate the data based on thermal property. Hence, it is used for particle classification and found it is more accurate. If there are multiple particles in a formulation, then ipvPHot is used to check particle melting point in the formulation, also used for contamination analysis.

ImageProVision provides a feature in ipvPClass for comparing the analysis of various batches or for the analysis of a single sample taken done at various stages it generates the comparing data and the overlapping graph which helps to identify the changes in morphological parameters between various analysis.

Yes, we have to reply to the general query, which USFDA asks for particle size and shape analysis.

Yes, we can measure the width of gelatin by removing capsule coting; there is a special application in our Software ipvPSA.

ImageProVision has an ipvProofCheck system for smart proofreading, this system is used for checking various printed material cartons, leaflets and labels, against the master copy or artwork. It works as artwork or master copy loaded in pdf format and it scans through a defined scanner i.e., roller scanner, or flat blat scanner.
The system contains a scanner system which converts sample material (paper material or sample, carton sample, leaflet sample and label sample) into digital format and with the help of ipvProofCheck software and its unique algorithm helps to compare pixels of Master copy to the pixel of resulted sample is possible).

Generally, every printed material i.e., carton, leaflet and label after printing by the big printing machines has crate some error. It is possible of errors during printing, like some letters missing, some drop marks, and colour mismatches. This entire mistake can be measured by using ImageProVision’s unique algorithm software ipvProofCheck.
ipvProofCheck system to smart proof-reading system is used for checking various printed materials cartons, leaflets and labels, against the master copy or artwork after artwork or master copy is loaded in pdf format of any printed material it scans through a defined scanner i.e., roller scanner, flat blat scanner. The printed scanner is converted into digital format and pixel-to-pixel comparison is done.

Generally, every printed material i.e., carton, leaflet and label has come up with different errors like data missing, ink marks, and mismatch of colors. All these mistakes can be measured by using ImageProVision software called ipvProofCheck. ipvProofCheck is work as a smart proofreading system for checking all kind of printed materials such as carton, leaflet and label against the master copy. The procedure of proofreading comes up in two-way, one pdf to pdf and another one is pdf to printed material scanning. The printed scanner converts printed material into digital format and pixel-to-pixel comparison is possible.

The Active Pharmaceutical Ingredient (API) is part of any kind of drug form (except dissolved API) that produces the intended effects. Some drugs, such as combination therapies, have multiple active ingredients to treat different symptoms or act in different ways. ipvPClass Particle size analysis classifier gives information based on particle distributed size in drug samples and also can be used to calculate different properties of a particle and how they will act under certain conditions. The particle size can affect the dissolving rate. Smaller API particles have a smaller surface area and will metabolise more quickly and Water-soluble APIs also dissolve at a faster rate if they have a smaller particle size. The pharmaceutical industry and API manufacturer uses all information while designing drugs. So, with ImageProVision software ipvPClass is essential for API manufacture for getting detailed information about API, Excipients, and other kinds of particles such as crystal particles, globules etc.

Observing the Cream sample and globule sample is difficult sometimes to analyse particle size with the help of laser diffraction because in laser diffraction the sample should be diluted form (i.e. not good for sensitive APIs which might get diluted while dissolving). Laser diffraction method the rays pass through the diluted solution and pick up the particles present in the solution but due to the ray falling on particles, it creates a certain angle of deviation by which the laser diffraction considers the particles as round shape or cylindrical shape (no other shape of particles was shown). While observing the cream samples under a microscope, first less amount of sample requirement, and no need to dilute the cream with dilution solvent, the observation of globules with IPV-developed software it becomes easy to analyse globules samples. The cream is in the semi-solid form it is difficult or not easy to flow in laser diffraction, and sometimes it may get problems. For any semi-solid material or topical material (cream, gel, aerosol, ointment etc.) for this microscopy analysis is very easy and accurate.

Particle characterization is the process of identifying various particles by particle shape, size, surface properties, charge properties, and structure. There is a broad range of commercially available particle characterization techniques that can be used to measure particulate samples. There are some techniques for all types of sample analysis:
Microscopy Image Analysis: The system comprises of a microscope, a digital camera and analysis software. A digital camera takes images of drug samples kept under the microscope and transfers to the connected computer. The software has unique algorithms to detect particles and calculate various parameters. It is a direct technique which measures 2D images of 3D particles. Image analysis gives a number-weighted distribution where each particle is given equal weighting irrespective of its size.
Laser Diffraction: Laser diffraction measures particle size distributions by measuring the angular variation in the intensity of light scattered as a laser beam passes through a dispersed particulate sample. Large particles scatter light at small angles relative to the laser beam and small particles scatter light at large angles. The angular scattering intensity data is then analyzed to calculate the size of the particles responsible for creating the scattering pattern, using the Mie theory of light scattering. The particle size is reported as a volume equivalent sphere diameter.
Dynamic Light Scattering: Dynamic light scattering (DLS), also known as Photon Correlation Spectroscopy (PCS) or Quasi-Elastic Light Scattering (QELS).This is an analytical technique used to measure the particle size distribution of protein formulations across the oligomer and sub-micron size ranges of approximately 1 nm to 1 µm.
Raman Spectroscopy: In Raman spectroscopy a laser is focused into the sample, the inelastic scattered radiation (Raman) is optically collected and directed into a spectrometer, which provides wavelength separation, and a detector converts photon energy to electrical signal intensity. The applications range from verification of raw materials to process monitoring of drug production to quality control of products. Similar to an infrared spectrum, a Raman spectrum consists of a wavelength distribution of peaks corresponding to molecular vibrations specific to the sample being analyzed.
Sieve Analysis: Sieve analysis is a technique used to determine the particle size distribution of a powder. This method is performed by sifting a powder sample through a stack of wire mesh sieves, separating it into discrete size ranges. A sieve shaker is used to vibrate the sieve stack for a specific period of time.
So, the best solution for particle characterization is Microscopy because it is clearly visible in size shape etc.

Microscopy analysis is considered to be a manual instrument it depends on the person who doing the activity or performing the analysis. To qualify the problem ImageProVision gives ipvPClass an in-built functionality that checks the balances so that the result is reproducible. So, with a lot of research, we have found that if we control three parameters:
No. of particles
Percentage of agglomerations
No. of images
So, for any sample, if we freeze this parameter then the result produces the ipvPClass. If your sample is the same, then the result is the same.

If yes then the IPV software’s are working awesome with any kind of compatible binocular and trinocular microscope (optical microscope, inverted microscope etc.). Also has lots of other software all are 21 CFR part 11 complaints some of them were following the LIMS complaint software that will make the analysis easier, time and costs efficient.

Yes, ImageProVision has two automated microscopic software
ipvAutoClass (Particle Size Analysis Classifier – for complete slide analysis followed by USP 776
ipvAutoCount (Automatic Particulate Matter Counter) – for complete filter paper analysis followed by USP 788 and USP 789

Particulate Matter Testing is required to analyse contamination in injectable and ophthalmic dosages, sometimes solid oral dosage form is also gone through contamination testing. It is possible by filter paper analysis followed by USP 788 & 789.

The use of filter membrane or paper to analyse the injectable or inhaler solution i.e., give in USP 788 & 789 where you need to know the Particulate matter counter, foreign particles or unwanted particles.

Lots of companies find it very difficult to track the microbial plates due to huge activity with microbial plates. They have to follow the complex process to track and trail all the details of the Patri plate with evidence images.

This process of track and trail of every petri plate with evidence images is possible through the ipvMicrobe – Microbial colony capturing system, System comprises two industrial cameras one is on the upper side and another one on the downside of the Petri hood. The lower camera is for scanning the bar code and the upper camera is for capturing the Petri plate images for evidence. The combination of the bar code and its petri image is stored in a stack, which next can be stored in LIMS (Laboratory Information management system) or other laboratory database systems like MODA.

Yes, 21 CFR part 11 compliance is required for a closed computerized system to avoid error and manipulation of data. ipvMicrobe software meets the criteria as per 21 CFR part 11 compliance and it gives more data security with the facility to connect with any Laboratory Information management system.

The analysis and evaluation of the size, shape, surface properties, and other characteristics of Active Pharmaceutical Ingredients (APIs) This analysis helps in understanding the physical attributes of APIs, which can impact their performance and behaviour in pharmaceutical formulations

A microscopy technique used to observe and analyse the behaviour of materials, especially pharmaceutical formulations, under controlled heating conditions Hot stage microscopy allows for the study of changes in sample properties at elevated temperatures

The reverse engineering process used to identify and quantify the components and their respective quantities in a pharmaceutical product Deformulation analysis helps to understand the formulation of a drug product, including its excipients and active ingredients

The analysis of the physical properties and characteristics of excipient particles used in pharmaceutical formulations. Understanding excipient particle propertie

The measurement and determination of the size of globules or dispersed oil droplets in semi-solid pharmaceutical dosage forms, such as creams and ointments Globule size affects product texture, stability, and drug release

The evaluation of seams or junctions in soft gelatin capsules Seam analysis is crucial in assessing the capsule’s integrity and preventing leakage or contamination of the encapsulated contents

The quantification and analysis of particulate matter collected on filter paper from a pharmaceutical sample. This analysis is important in assessing pharmaceutical products’ cleanliness and particulate contamination.

This refers to examining and understanding particles’ properties at a microscopic level. It involves determining attributes such as size, shape, composition, and distribution of particles.

A device used to measure the size of particles at a microscopic level. It utilises various techniques such as light scattering, laser diffraction, or image analysis to determine the size distribution of particles in a sample.

This system uses automated algorithms to categorise particles based on predefined criteria. It can help identify and classify particles according to their characteristics, such as shape, size, and composition.

A tool designed to count and quantify particulate matter (tiny solid particles or liquid droplets suspended in the air) at a microscopic scale. This is crucial for environmental monitoring and air quality assessment.

The study of particles at the nanometer scale, typically ranging from 1 to 100 nanometers in size. Nanoparticle analysis involves examining properties such as size, shape, surface area, and potential applications in various fields, including medicine and materials science.

The thermal analysis technique is thermogravimetric analysis (TGA), which is used to study how a material’s properties change with temperature.

A tool automatically or manually counts the number of microbial colonies grown on a culture medium. This is a common technique in microbiology to estimate the concentration of microorganisms in a sample.

Starch Gelatinization is a process of breaking down the intermolecular bonds of starch molecules in the presence of water and heat. Pregelatinized starch derives primarily from corn, potato, maize and tapioca. It is then cooked and dried. Instant puddings, pie fillings, salad dressings, candy often contain pregelatinized starch.