Research
 

Research has always been driving force behind Softmusk Solutions. Because there are so many possibilities and there is so much yet to be done, we believe innovations that improve lives. Students and researchers working on below subjects can contact us at. projects@softmusk.com


Brain Tumor Detection in MRI Images
Medical image processing is the most challenging and emerging field now a days. Processing of MRI images is one of the part of this field. This work describes the strategy to detect & extract brain tumour from patient’s MRI scan images of the brain. This application incorporates some noise removal functions, segmentation and morphological operations which are the basic concepts of image processing. Detection and extraction of tumour from MRI scan images of the brain is done by using MATLAB software. Read more...
 
Content Based Image Retrieval Using Mobile Agents and Steganography
An approach for image retrieval. Based on steganography and mobile agents. By utilizing the information hiding technique, the valuable image attributes are hidden in an image without degrading the image quality. A centralized indexing system of multiple image archives is an essential component of this approach. Java based mobile agents manage the query phase of the system. Based on the simulation results, the system wiil not only show the efficiency in hiding the attributes but also provide other advantages such as: (1) fast transmission of the retrieved image to the receiver, (2) searching made easy. Read more...
 
Face Recognition using Neural Network
Automatic recognition of people is a challenging problem which has received much attention
during recent years due to its many applications in different fields. Face recognition is one of those challenging problems and up to date, there is no technique that provides a robust solution to all situations. Here we present a new technique for human face recognition. This technique uses an image-based approach towards artificial intelligence by removing redundant data from face images through image compression using the two-dimensional discrete cosine transform (2D-DCT).

The DCT extracts features from face images based on skin color. Featurevectors
are constructed by computing DCT coefficients. A self-organizing map (SOM) using an unsupervised learning technique is used to classify DCT-based feature vectors into groups to identify if the subject in the input image is “present” or “not present” in the image database. Read more...
 
Fragile Watermarking For Authentication Of Images
Digital watermarking research has generally focused upon two classes of watermarks, fragile and robust. Robust watermarks are designed to be detected even after attempts are made to remove them. Fragile watermarks are used for authentication purposes and are capable of detecting even minute changes of the watermarked content. Read more...
 
Iris Recognition for Personal Identification
With the need for security systems going up, Iris recognition is emerging as one of the important methods of biometrics-based identification systems. This project basically explains the Iris recognition system developed by John Daugman and attempts to implement this algorithm in Matlab, with a few modifications. Read more...
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