Currency Recognition Using Image Processing Matlab Project with Source Code

ABSTRACT

                  The Reserve Bank is the one which issue bank notes in India. Reserve Bank, changes the design of bank notes from time to time. Reserve bank uses several techniques to detect fake currency. Common people faces many problems for the fake currency circulation and also difficult to detect fake currency, suppose that a common people went to a bank to deposit money in bank but only to see that some of the notes are fake, in this case he has to take the blame. As banks will not help that person. Some of the effects that fake currency has on society include a reduction in the value of real money; and inflation due to more fake currency getting circulated in the society or market which disturbs our economy and growth - an some illegal authorities an artificial increase in the money supply,a decrease in the acceptability of paper money and losses. Our aim is to help common man to recognize currency. Proposed system is based on image processing and makes the process automatic and robust. Shape information are used in our algorithm. Original Note Detection Systems are present in banks but are very costly. We are developing an image processing algorithm which will extract the currency features and compare it with features of original note image. This system is cheaper and can provide accuracy on the basics of visual contents of note.

PROJECT OUTPUT

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Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Matlab Project for FingerPrint Recognition and Matching Using Image Processing

ABSTRACT

                 The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae from the thinned image. Fingerprint is a very vital concept in making us completely unique and can not be altered. It is necessary to recognize fingerprint in proper manner. Here we are trying to recognize the fingerprint image samples by using minute extraction and minute matching techniques. In minute extraction it counts the crossing numbers and from the count it will be classified as normal ridge pixel, termination point and bifurcation point. Then the input finger print data is compared with the template data. This is called as minute matching. 

                    Biometric systems operate on behavioral and physiological biometric data to identify a person. The behavioral biometric parameters are signature, gait, speech and keystroke, these parameters change with age and environment. However physiological characteristics such as face, fingerprint, palm print and iris remains unchanged through out the life time of a person. The biometric system operates as verification mode or identification mode depending on the requirement of an application. The verification mode validates a person’s identity by comparing captured biometric data with ready made template. The identification mode recognizes a person’s identity by performing matches against multiple fingerprint biometric templates. Fingerprints are widely used in daily life for more than 100 years due to its feasibility, distinctiveness, permanence, accuracy, reliability, and acceptability. Fingerprint is a pattern of ridges, furrows and minutiae, which are extracted using inked impression on a paper or sensors. A good quality fingerprint contains 25 to 80 minutiae depending on sensor resolution and finger placement on the sensor. The false minutiae are the false ridge breaks due to insufficient amount of ink and cross-connections due to over inking. It is difficult to extract reliably minutia from poor quality fingerprint impressions arising from very dry fingers and fingers mutilated by scars, scratches due to accidents, injuries. 

PROJECT OUTPUT

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Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Matlab Project for Brain Tumor Detection Using Watershed Technique

ABSTRACT

             In the field of medical image processing, detection of brain tumor from magnetic resonance image (MRI) brain scan has become one of the most active research. Detection of the tumor is the main objective of the system. Detection plays a critical role in biomedical imaging. In this project, MRI brain image is used to tumor detection process. This system includes test the brain image process, image filtering, morphological operation, Detection of the tumor, Finding Tumor Stage and determination of the tumor location. In this system, morphological operation of watershed technique is applied to detect the tumor. The detailed procedures are implemented using MATLAB. The proposed method extracts the tumor region accurately from the MRI brain image. The experimental results indicate that the proposed method efficiently detected the tumor from the brain image. Watershed Segmentation is the best methods to group pixels of an image on the basis of their intensities. Pixels falling under similar intensities are grouped together. Watershed is a mathematical morphological operating tool. Watershed is normally used for checking output rather than using as an input segmentation technique because it usually suffers from over segmentation and under segmentation. The watershed techniques are useful for segmentation of brain tumor. Image segmentation is based on the division of the image into regions. Division is done on the basis of similar attributes. 

PROJECT OUTPUT

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Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Target Detection Using Image Processing Matlab Project with Source Code

ABSTRACT

             Target detection using image processing the automatic detection and marking of target objects will improve the efficiency of remote sensing image interpretation.  Target detection refers to the use of high spectral resolution remotely sensed images to map the locations of a target or feature (often a plant species of interest) with a particular spectral or spatial signature. Target detection or feature extraction encompasses a broad range of techniques, including measurements derived from individual bands and more complex methods designed to recognize discrete features by shape, hyperspectral signature, or texture. Targets of interest are often smaller than the pixel size of the image (subpixel target detection) or are mixed with other nontarget cover types within a pixel, requiring techniques such as spectral mixture analysis to detect the target species. Hyperspectral images are useful in target detection because they contain a large contiguous set of spectral bands, often numbering in the hundreds to thousands, and provide large quantities of high spectral resolution data. Using a hyperspectral image, the spectral properties of the target, such as contrast, variability, similarity and discriminability, can be used to detect targets at the subpixel level. The user specifies spectral endmembers, which are the reflectance spectra of the “pure” targets that occur across the landscape, and image processing software is used to characterize the extent of the target across the landscape. The selection of spectral endmembers is similar to the idea of identifying training areas in supervised classification, but the spectral endmember can then be used at a subpixel level to detect the species of interest. Spectral endmembers are often generated in the field using a field spectroradiometer. Then the image is processed using classification algorithms to detect the locations of the target species.

PROJECT OUTPUT

PROJECT VIDEO

Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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