Blood Group Detection Using Image Processing Matlab Project Code

ABSTRACT

          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. The slide test consists of the mixture of one drop of blood and one drop of reagent, being the result interpreted according to the occurrence or not of agglutination. The combination of the occurrence and non occurrence of the agglutination determines the blood type of the patient. 

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Mr. Roshan P. Helonde

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Cheque Number Recognition Using Image Processing Full Matlab Project Code

ABSTRACT

          Now a days CTS bank cheques are commonly used for many financial transactions globally and processed by clearance branches by using the distinct cheque number of the corresponding bank. The proposed work focuses on segmentation and recognition of bank cheque number using optical character recognition and statistical correlation function. In general bank cheques contain the cheque number at left bottom region which will be considered as the potential area for locating and segmenting the cheque number. A standard template of numerical digits will be created from 0 to 9 for matching with the test samples using standard statistical correlation function. The manual database will be created of bank cheque images including bank cheques are used for number recognition. The accuracy of the system is analyzed by the variation on the range of the cheque image with cheque number having different font, size, quotes and varieties of characters with noise. The efficiency of the system is evaluated through the experimental results extensively. 

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Mr. Roshan P. Helonde

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Lung Cancer Detection Using Image Processing Full Matlab Project Code

ABSTRACT

        Lung cancer prevalence is one of the highest of cancers, at 18 %. One of the first steps in lung cancer diagnosis is sampling of lung tissues or biopsy. These tissue samples are then microscopically analyzed. This procedure is taken once imaging tests indicate the presence of cancer cells in the chest. Lung cancer diagnosis using lung images. One of them is that doctor still relies on subjective visual observation. A medical specialist must do thorough observation and accurate analysis in detecting lung cancer in patients. Hence, there is need for a system that is capable for detecting lung cancer automatically from microscopic images of biopsy. This method will improve the accuracy and efficiency for lung cancer detection. The aim of this research is to design a lung cancer detection system based on analysis of microscopic image of biopsy using digital image processing. Microscopic images of biopsy are feature extracted with the Gray Level Co-Occurrence Matrix (GLCM) method and classified using back propagation neural network. This method is implemented to detection of lung cancer of lung samples.

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Mr. Roshan P. Helonde

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Currency Recognition Using Image Processing Full Matlab Project Code

ABSTRACT

           The appearance of the currency is part of this development and it is affected directly, where there is exploited in incorrect form by copying the currency in a manner similar to the reality. Therefore, it became necessary to implement a proposal for being a suitable as solution not inconsistent with the different cultures, time and place. This clear through add the watermarks inside currency, which is difficult to be copied. At the same time, this watermarks may be visible to the naked eye so can easily inferred or it is invisible. However the high resolution imaging devices can copy these additions. In this research, we have proposed a system to distinguish the currencies by the program that working a submission inferred to the watermark by feature extraction determined the type of currency. In addition to, it determined category of the currency. Benefit of it, is reducing as much as possible the spread of counterfeit currency and this system can be used by any user wants to make sure of the currency.

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Mr. Roshan P. Helonde

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Melanoma Detection / Skin Cancer Detection Using Image Processing Full Matlab Project Code

ABSTRACT

         Skin cancer – also known as malignant melanoma – is one of the deadliest form of cancer if not recognized in time. Since the pigmented areas/moles of the skin can be nicely observed by simple, non-invasive visual inspection (e.g. by a dermatoscope), the clinical protocols of its recognition also consider several visual features. Melanoma is the deadliest form of skin cancer, which is considered one of the most common human malignancies in the world. Early detection of this disease can affect the result of the illness and improve the chance of surviving. The tremendous improvement of deep learning algorithms in image recognition tasks promises a great success for medical image analysis, in particular, melanoma classification for skin cancer diagnosis. Activation functions play an important role in the performance of deep neural networks for image recognition problems as well as medical image classification. Melanin is the pigment that discerns the color of human skin. The special cells produce melanin in the skin. If these cells are damaged or unhealthy, skin discoloration is visible. Skin pigment discoloration on cheeks is a hazardous fact as a symptom of human skin disease with a possibility of losing natural beauty. The extracted information of the skin discoloration can work as a guide to diagnosis the disease. In this research, different imaging techniques like watershed method, edge detection and morphological operations are used to analyze and extract the information of cheek’s discoloration lesion by measuring the pixel number of lesion on skin. The image analyzing results are visually examined by the skin specialist and are observed to be highly accurate. The visual results are presented in the description and the accuracy of mathematical analysis is 94.88 percent.

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Mr. Roshan P. Helonde

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Audio Steganography Using Image Processing Matlab Project Code

ABSTRACT

            Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message, a form of security through obscurity. Steganography works by replacing bits of useless or unused data in regular computer files (such as graphics, sound, text, HTML, or even floppy disks ) with bits of different, invisible information. This hidden information can be plain text, cipher text, or even images. The rapid development of multimedia and internet allows for wide distribution of digital media data. It becomes much easier to edit, modify and duplicate digital information. Besides that, digital documents are also easy to copy and distribute, therefore it will be faced by many threats. It is a big security and privacy issue, it become necessary to find appropriate rotation because of the significance, accuracy and sensitivity of the information. Steganography and Cryptography are considered as one of the techniques which are used to protect the important information, but both techniques have their pro’s and con’s. In this proposed system of audio steganography we have implemented a new scheme based on mel frequency components. The mel frequency cepstrum coefficients are used for finding the unique feature audio data in audio file. The returned features provide us with highly robust and high end features with low invariance. We have used this property of MFCC in order to detect high bandwidth free space location in the sound data and have embedded the encrypted watermark image data into these MFCC components. The proposed scheme works to increase the PSNR values and reduce the error rate of hiding the data in the image and thus improves the sound quality and makes it look original. The effect of MFCC is positive as the watermark extracted from this proposed scheme shows high correlation to the original watermark and also the resistance towards various attacks has also been improved, the attacks degrade the watermark due to high payload or bigger watermark size, the probability of extraction of watermark or steganograph data becomes higher.

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Mr. Roshan P. Helonde

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Cotton Leaf Disease Detection and Classification Using Image Processing Full Matlab Code

ABSTRACT

            Cotton is one of the most important fiber crop which is used as raw material in textile industries. But, now-a-days cotton is facing number of problems related to the healthy growth of crop due to diseases. These diseases are reducing the productivity of cotton crop and farmers are getting suffered financially due to this crop loss. Agriculture is an important source of livelihood where 65% population is depend on it. The crop loss due to disease is increasing day by day which affects on the quality and productivity of crop. As diseases on the crop are certain, the early disease detection of the crop plays major role to control the loss in agriculture. In the proposed disease detection system, the work is carried out on cotton leaves. Initially the infected region is captured and pre-processed. During segmentation, leaf as well as diseased part is segmented using k means clustering method and different features are extracted such as color and texture with the help of color-co-occurrence method. Finally classification technique is used for detecting the diseases with the help of SVM (Support Vector Machine) classifier.

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Mr. Roshan P. Helonde

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WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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