Anushikha Singh

Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image

Glaucoma is a disease of the retina which is one of the most common causes of permanent blindness worldwide. This paper presents an automatic image processing based method for glaucoma diagnosis from the digital fundus image. In this paper wavelet feature extraction has been followed by optimized genetic feature selection combined with several learning algorithms and various parameter settings. Unlike the existing research works where the features are considered from the complete fundus or a sub image of the fundus, this work is based on feature extraction from the segmented and blood vessel removed optic disc to improve the accuracy of identification. The experimental results presented in this paper indicate that the wavelet features of the segmented optic disc image are clinically more significant in comparison to features of the whole or sub fundus image in the detection of glaucoma from fundus image. Accuracy of glaucoma identification achieved in this work is 94.7% and a comparison with existing methods of glaucoma detection from fundus image indicates that the proposed approach has improved accuracy of classification.

Blood vessel inpainting based technique for efficient localization and segmentation of optic disc in digital fundus images

Abstract The Optic disc (OD) nerve head region in general and OD center coordinates in particular form basis for study and analysis of various eye pathologies. The shape, contour and size of OD is vital in classification and grading of retinal diseases like glaucoma. There is a need to develop fast and efficient algorithms for large scale retinal disease screening. With this in mind, this paper present a novel framework for fast and fully automatic detection of OD and its accurate segmentation in digital fundus images. The methodology involves optic disc center localization followed by removal of vascular structure by accurate inpainting of blood vessels in the optic disc region. An adaptive threshold based Region Growing technique is then employed for reliable segmentation of fundus images. The proposed technique achieved significant results when tested on standard test databases like MESSIDOR and DRIVE with average overlapping ratio of 89% and 87%, respectively. Validation experiments were done on a labeled dataset containing healthy and pathological images obtained from a local eye hospital achieving an appreciable 91% average OD segmentation accuracy.

Digital identification tags for medical fundus images for tele-ophthalmology applications

This paper proposes a method of inserting a digital pattern having patient identity in the medical image without tampering the medical information of the image. To attain imperceptible insertion of the digital pattern a frequency domain approach is used in the mid frequency band of the discrete cosine transform. The original medical image and the stego-image is compared and analyzed for all features and also tested for retaining of all features and medical information. Blood vessels have been extracted from the original and stego image and it has been established from experimental results that the features remains unaltered. Texture features also has been analyzed and experimental results indicates that the variation in the texture features is minimal and do not affect the medical information. The correlation of the features extracted is above 0.99 indicating the insertion of the digital pattern did not cause any loss of medical information in the image.

Generation of biometric based unique digital watermark from iris image

This paper proposes a proficient digital watermark generation technique from biometric data which will be unique and can be logically owned to prove ownership. The biometric pattern of iris is used to generate the digital watermark that has a clear stamp of ownership. The generated watermark has been studied for uniqueness and identification and has been used to watermark audio signals. Dither modulation quantization is applied on the singular values of Singular Value Decomposition domain for embedding the watermark. Experimental results indicates that the watermark can survive the signal processing attacks such as Gaussian noise corruption, re-sampling, re-quantization, cropping, and compression and maintain the perceptual properties of the host signal and hence satisfies the design requirements of digital watermarking. The extracted biometric based watermark was uniquely identified under signal processing attacks.

A computer vision based technique for identification of acrylamide in potato chips

Display Omitted An image processing method for acrylamide identification in potato chips.Image features are extracted strategically from potato chip segmented image.Dimension reduction algorithms are used for prominent feature selection.Acrylamide identification is done using supervised classification algorithm.Accuracy of acrylamide identification achieved in this work is 94%. Acrylamide is a well-known neurotoxin substance commonly found in fried and baked food items such as potato chips, cookies, biscuits & French fries. Identification of such toxic chemicals in fried food is of great importance. Conventional methods of acrylamide identification in food items are time consuming, expensive and may need specialized manpower. The proposed work presents a computer vision based non-destructive method to identify the presence of acrylamide in potato chips. The proposed method is based on analysis and classification of the discriminatory features of the image in spatial domain. The potato chips are automatically segmented from the image followed by statistical and texture features extraction from the segmented image in spatial domain. These statistical features are then analyzed for identification of acrylamide content using support vector machine (SVM) classifier. The discriminatory variation in the features of the image is strategically related to the presence of acrylamide using image processing techniques. The experimental results have shown accuracy over than 94% and sensitivity of 96% indicating that this method could be explored for viable commercial use.

An efficient automatic method of Optic disc segmentation using region growing technique in retinal images

Segmentation of Optic disc (OD) from a retinal image is a essential step while developing automated screening systems for eye disease like diabetic retinopathy, Glaucoma etc. This paper proposes a method of automatic optic disk segmentation based on region growing technique with automatic seed selection. In this method centre of optic disk is considered as a seed to apply region growing technique to segment the optic disk from the preprocessed retinal image. Automatic detection of centre of optic disk is done by double windowing method. The algorithm uses image processing techniques like contrast adjustment, morphological operations & filtering to process the retinal image and to remove the blood vessels from the retinal image. The performance of optic disk segmentation by proposed method is compared with Optic disk segmentation by ophthalmologists and results are found convincing and efficient. The experimental results indicate this method of segmentation of the OD has good accuracy and also is computationally cheap.

Watermark generation from fingerprint features for digital right management control

The conventional digital watermarking schemes uses an arbitrary digital pattern as the watermark which has limitations in proving ownership of the watermark. This paper proposes a proficient digital watermark generation technique from biometric data which will be unique and can be logically owned to prove ownership. The issue of ownership watermark is addressed in this paper. The biometric pattern of fingerprint is used to generate the digital watermark that has a stamp of ownership. The generated watermark has been studied for uniqueness and identification and has been used to watermark digital images. Discrete cosine transformation is used for embedding the watermark in the image. Experimental results indicate that the watermark can survive the signal processing attacks and maintain the perceptual properties of the host signal. The extracted biometric based watermark was uniquely identified under signal processing attacks by matching of the feature points.

Automatic exudates detection in fundus image using intensity thresholding and morphology

Diabetic retinopathy (DR) is a leading cause of blindness in diabetic patients. Exudates are one of the most common earliest signs of diabetic retinopathy. Automatic and accurate detection of exudates in fundus images is an important step in early diagnosis of DR. In the proposed method detection of exudates, two independent approaches based on intensity thresholding and morphological processing are strategically combined to detect any small exudates present while removing all possible types of false positives. This strategic combination removes the noise sources from blood vessels and reflections during image capture making the detection of exudates accurate. Experimental results indicate that the proposed method has good accuracy in exudates detection without compromising the computational time and hence can be considered for screening purpose of DR.

Digital ownership tags based on biometric features of iris and fingerprint for content protection and ownership of digital images and audio signals

This paper is aimed to address the issue of ownership rights of digital data like images and audio signals. This is achieved by inserting a perceptually transparent unique digital pattern in the digital host signal. The digital pattern is generated by a methodical fusion of features extracted from iris image and fingerprint image. The fusion is done in such a way that the individual templates can be later decomposed from the digital pattern and can be used for identification. The pattern is optimized to a size which has acceptable payload under the perceptual transparency constraints of design requirements. The embedding is done using the singular value decomposition method for the audio signals and using discrete cosine transform method for the images. The recovered pattern is subjected to decomposition to individual templates, i.e. fingerprint and iris templates which were subjected to unique identification tests. Experimental results indicate that the embedding of the digital tag in the image or audio do not tamper the perceptual transparency and is also robust to signal processing attacks. The SNR of the watermarked signal is very good and the BER and Normalized correlation of the extracted watermark are very encouraging. The templates which were decomposed from the extracted digital watermark were mapped for unique identification even under serious attacks. Use of two biometric features for generating a digital watermark is a novel attempt for accurate identification of ownership of the digital data as these biometric features will be unique for every subject and hence this can be considered as a significant development towards digital right management (DRM) control.

Unique identification code for medical fundus images using blood vessel pattern for tele-ophthalmology applications

BACKGROUND AND OBJECTIVE Identification of fundus images during transmission and storage in database for tele-ophthalmology applications is an important issue in modern era. The proposed work presents a novel accurate method for generation of unique identification code for identification of fundus images for tele-ophthalmology applications and storage in databases. Unlike existing methods of steganography and watermarking, this method does not tamper the medical image as nothing is embedded in this approach and there is no loss of medical information. METHODS Strategic combination of unique blood vessel pattern and patient ID is considered for generation of unique identification code for the digital fundus images. Segmented blood vessel pattern near the optic disc is strategically combined with patient ID for generation of a unique identification code for the image. RESULTS The proposed method of medical image identification is tested on the publically available DRIVE and MESSIDOR database of fundus image and results are encouraging. CONCLUSIONS Experimental results indicate the uniqueness of identification code and lossless recovery of patient identity from unique identification code for integrity verification of fundus images.