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Swetha sharma Team Leader -(Technical), HSP Labs
 
Swetha sharma's Profile
Swetha sharma
Team Leader -(Technical), HSP Labs
HSP Labs
confidential
confidential
Chennai, India
Toostep 
Professional summary
Swetha sharma's Experience
Current :

Team Leader -(Technical), HSP Labs
IT Products
India, Chennai

Working from 2004

Previous :

Staff Engineer , Software, Formerly Purple Vision Technologies Pvt Ltd
Bangalore

Worked from 2007 to 2012

Brief summary :

Designation: Staff Engineer, Software Department: Research and Development Team. Company : TES -PV Electronics Solutions, Bangalore (Formerly Purple Vision Technologies Pvt Ltd) Duration : 2 yrs 3mnths (as on 03.03.07) Current Project: Systems Design Configuration Management ( Feb 07 - till date)

Previous :

Image Acquisition

Worked from 2006 to 2006

Brief summary :

A Device driver is hardware -dependent program which enables another typically an operating system or an application specific software package to interact transparently with the device. There are various device drivers developed for various hardware and the system which I am developing should work on the available modules and generate an off-the-shelf loadable image based on the hardware designed. This helps in reducing time to market for development of new Custom Design Boards based on available modules developed earlier. Environment: VC++ (MFC) Responsibility: Application Development for the whole system. Project 2: Algorithm for Image Acquisition ( Jul06 - Oct06) Module1: Algorithm Development This algorithm is targeted for a camera. A digital camera captures image of the focused object by exposing a CCD (charged coupled device).This sensor which is sensitive to red, blue and green components of light stores only partial raw data of the complete image. So, viewing the complete image requires interpolation of the values inputted by the sensor .This method of interpolating the values is called Demosaicing. I was involved in developing an algorithm for optimal way of interpolating the values.

Previous :

Project 3: Face Recognition

Worked from 2005 to 2006

Brief summary :

Environment: Matlab 6.0 Module2:Testing of the Algorithm A test application was developed giving an RAW file as input, which gives an output as .bmp file Environment: VC++ (MFC) Responsibility: Identify an algorithm for de-mosaic and simulation of the algorithm. The algorithm uses a weighted matrix which is applied in the neighborhood elements and reconstructs the image. Testing of the algorithm by developing an test application. Project 3: Face Recognition ( Dec05 - Jun06) Face recognition is a problem of identifying or verifying a person or group of people from a large database, when a still image or a video is given as input. The analysis requires the lighting conditions to be controlled, detect a face of a person from group and elimination of the background. This phase is known as the preparatory phase for the analysis of a face. I was involved in identifying the methods and generation of the algorithm. Module1: Development of a Mathematical Model Contrast Stretching Contrast Stretching is an image enhancement technique for improving contrast and brightness of an image. This involves upgrading of the image values based on a Histogram, a mathematical analysis of the intensity values of the image. Environment: Matlab 6.0 Responsibility: The system is described by a probability of the occurrence of a pixel value in the intensity range. The intensity values are stretched by operating on the histogram. Image Zoom. Scaling is a process of increasing or decreasing the resolution of an image. Sub module 1: Analysis of standard algorithms Environment: Matlab 6.0 Responsibility: Identify techniques for implementation of scaling and simulation of the algorithm. This activity is a part of the study and design phase for the development of the new algorithm. Sub module 2: Development of an algorithm for Scaling Environment: Matlab 6.0 Responsibility: Developed an algorithm using splines function and showcased the same using Matlab simulations. Edge-detection Edge-detection is a technique of identifying the color gradient in an image and tracing the path of gradation. Environment:

Previous :

MFC Project 4: LUT Generation And Tuning

Worked from 2005 to 2005

Brief summary :

Matlab 6.0 Responsibility: Simulation of canny-edge detection algorithm. Module 2: Testing Phase A test application was developed which takes an image as input, and outputs an image whose contours are detected, contrast is improved and the pixel resolution is improved. Environment: VC++ (MFC) Project 4: LUT Generation and Tuning ( Feb05 - Sep05) Client:

 
 
 
 
Swetha's communities
IIT Madras
562 members, 21 jobs, 38 articles, 1 questions, 8 debates, 5 idea contests.
Image Processing - Changing frontiers
420 members, 1 jobs, 9 articles, 16 questions, 4 debates, 3 idea contests.
Recruitments Oppurtunities Through ABC Consultants For Technology/Telecom Sector in India
575 members, 311 jobs, 250 articles, 32 questions, 6 debates, 3 idea contests.
Swetha's contributions
Hi,  I have a friend who has 4+yrs of experience in Embedded firmware currently working in Bangalore. He has to shift to chennai urgntly due to personal reasons. How is the opportunity in  chennai for embedded technologies. rgds swetha   
Hello, What kind of an image do you have?  If it is a binary image you interchange the values 0 and 1,If it is a gray scale image subtract the values from 255.If it is a color image you have find the background pixels and change the value of the pixel...
 
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