Saturday, 16 February 2019

MATLAB code of Audio Denoising Using Hard and Soft Threshold


Noises present in communication channels are disturbing and the recovery of the original signals from the path without any noise is very difficult task. This is achieved by denoising techniques that remove noises from a digital signal. Many denoising technique have been proposed for the removal of noises from the digital audio signals. But the effectiveness of those techniques is less. In this Post, an audio denoising technique based on wavelet transformation is implemented.

Friday, 26 October 2018

MATLAB code for Optical Character Recognition


Optical Character Recognition plays most important role in the field of Recognition.  In this post we make people aware with how to implement Optical character recognition in MATLAB?
Normally in OCR we do Character recognition we the help of various image processing techniques like thresholding, segmentation and morphology. The steps involved in recognition is as follows.

Thursday, 25 October 2018

MATLAB code for Blood Group Detection using Image Processing


Blood Group Detection is most important aspect in medical field. determining of blood types is very important during emergency situation before administering a blood transfusion. Presently, these tests are performed manually by technicians, which can lead to human errors. Determination of the blood types in a short period of time and without human errors is very much essential. A method is developed based on processing of images acquired during the slide test. The image processing techniques such as thresholding and morphological operations are used. The images of the slide test are obtained from the pathological laboratory are processed and the occurrence of agglutination are evaluated. Thus the developed automated method determines the blood type using image processing techniques. The developed method is useful in emergency situation to determine the blood group without human error.

Wednesday, 31 January 2018

Medical image Fusion using PCA, DWT, PCA + DWT (Dicom Format)

Medical image Processing gain much importance in today's era. Here we are posting Mediacal image Fusion in DICOM format.

IMAGE FUSION:
Image Fusion is a process of combining the relevant information from a set of images of the same scene into a single image and the resultant fused image will be more informative and complete than any of the input images.
Input images could be multi sensor, multimodal, multi focus or multi temporal. There are some important requirements for the image fusion process:

Tuesday, 26 April 2016

MATLAB code of Real-time Object Tracking through Webcam (Robust Mean Shift Tracking with Corrected Background-Weighted Histogram)

Real-Time Object Tracking Through Webcam:

Object tracking is an important task in computer vision. Many algorithms have been proposed to solve the various problems arisen from noises, clutters and occlusions in the appearance model of the target to be tracked. Among various object tracking methods, the mean shift tracking algorithm is a popular one due to its simplicity and efficiency. Mean shift is a non parametric density estimator which iteratively computes the nearest mode of a sample distribution. After it was introduced to the field of computer vision, mean shift has been adopted to solve various problems, such as image filtering, segmentation and object tracking. In the mean shift tracking algorithm, the color histogram is used to represent the target because of its robustness to scaling, rotation and partial occlusion. 

Monday, 25 April 2016

MATLAB code of Object Tracking from Video (Robust Mean Shift Tracking with Corrected Background-Weighted Histogram)

Object tracking is an important task in computer vision. Many algorithms have been proposed to solve the various problems arisen from noises, clutters and occlusions in the appearance model of the target to be tracked. Among various object tracking methods, the mean shift tracking algorithm is a popular one due to its simplicity and efficiency. Mean shift is a non parametric density estimator which iteratively computes the nearest mode of a sample distribution. After it was introduced to the field of computer vision, mean shift has been adopted to solve various problems, such as image filtering, segmentation and object tracking.