Статьи журнала - International Journal of Image, Graphics and Signal Processing
Все статьи: 1110
Статья научная
We are proposing a novel algorithm for tracking human face(s) in different background video sequences. We have trained both face and non-face images which help in face(s) detection process. At first, FAST features and corner points are extracted from the detected face(s). Further, mid points are calculated from corner points. FAST features, corner points and mid points are combined together. Using the combined points, point tracker tracks face(s) in the frames of the video sequence. Standard metrics were adopted for measuring the performance of the proposed algorithm. Low resolution video sequences with challenges such as partial occlusion, changes in expression, variations in illumination and pose took part while testing the proposed algorithm. Test results clearly indicate the robustness of the proposed algorithm on all different background challenging video sequences.
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Imaging Techniques for Cancer Diagnosis and Scope for Enhancement
Статья научная
Imaging techniques are used to create images of structure, function and pathology of human body organs for cancer diagnosis. Various imaging techniques like X-ray, Ultra-Sonography (US), Positron Emission Tomography (PET), Ultrasound, MRI etc. are used for cancer diagnosis. These imaging techniques have gone through Lot of advancements during lost few years. These techniques vary in the technology and application. Various artifacts exist in these imaging techniques and images produced by theses imaging techniques. These artifacts can be exploited to enhance the imaging technique and the images produced by them.
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Implementation of Hand Sign Recognition for Non-Linear Dimensionality Reduction based on PCA
Статья научная
Hand Sign or gesture recognition is the way of communication for hearing and speech impaired people. Gestures are formed from motion of body or state but commonly initiate from the hand and face. Speech and gestures are the expressions; these are the communication medium between human beings. Hand gesture is movement or motion of human hand. Gesture recognition is mathematical interpretation of human hand by using computing devices. There are different sign languages used in all over world and have its own grammar structure. Even in India has different languages used in every state, sign languages has little difference in contra dictionary region. Hand sign recognition is used for robot control applications and sign language interpretation.
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Статья научная
Future high resolution instrument planned by ISRO for space remote sensing will lead to higher data rates because of increase in resolution and dynamic range. Hence, image compression implementation becomes mandatory. Presently designed compression technique does not take account of imaging system noise like photon noise etc. This ignorance affects compression system performance. As a solution, this paper proposes MLG (Multi Linear Gain) operation prior to main compression system. With digital MLG operation, captured image can be optimally adjusted to systems noise. Proposed MLG operation improves compression ratio. Simulation results show 15-30% improvement in lossless compression ratio. However this improvement depends on MLG gains and corner points which can be driven by system SNR plot. MLG operation also helps in improving SNR at lower radiance input, when lossy JPEG2000 compression is used as main compression. Up to 1-6 dB SNR improvement is observed in simulations. Proposed MLG implementation is of very low complexity and planned to be used in future missions.
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Статья научная
This paper presents, complete step by step description design and implementation of a high speed technique for character segmentation of license plate based on thresholding algorithm. Because of vertical edges in the plate, fast Sobel edge detection has been used for extracting location of license plate, after stage edge detection the image is segmented by thresholding algorithm and the color of characters is changed to white and the color of background is black. Then, boundary’s pixels of license plate are scanned and their color is changed to black pixels. Afterward the image is scanned vertically and if the number of black pixels in a column is equal to the width of plate or a little few, then the pixels of that column is changed to white pixel, until create white columns between characters, in continue we change pixels around license plate to white pixels. Finally characters are segmented cleanly. We test proposed character segmentation algorithm for stage recognition of number by code that we design. Results of experimentation on different images demonstrate ability of proposed algorithm. The accuracy of proposed character segmentation is 99% and average time of character segmentation is 15ms with thresholding algorithm code and 0.7ms only segmentation character code that is very small in comparison with other algorithms.
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Implementing Blind De-convolution with Weights on X-ray Images for Lesser Ringing Effect
Статья научная
X-rays and other medical images are distorted because of the limitations of the Imaging system. The other source from where the distortions get in are the transmission channels. The distortions are generally noise and blur. Unless and until the medical images are free of noise and blur they cannot be used by medical professionals to the full extent for diagnosis purpose. Therefore these images must be restored properly before they are used for diagnosis purpose. There are different restoration techniques out of which one is Blind Image Deconvolution. X-ray images restored with this technique have ringing effect in them. Using edgetaper (matlab function) prior to Blind Image Deconvolution reduces the ringing effect to an extent. This paper presents Blind Deconvolution algorithm with weights which gives lesser ringing effect in X-ray images when they are restored.
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Implementing of microscopic images mosaic revising algorithm
Статья научная
Microscopic image mosaic stitches several adjacent images into an integrated seamless picture, and is of significant practical value to remote medicine applications, especially in remote diagnosis. However, due to limitation in image acquisition method, a mismatch could occur as a result of variance in adjacent image stitching data and accumulation of errors. The current image stitching method still has room for improvement regarding processing speed and effectiveness, particularly in precision. In this paper, we proposed a new image mosaic revising algorithms based on the relativity of adjacent images and expounding the principal and equations on image mosaic error revising, as well as achieving automatic intelligent calculation with the revised algorithm. Through experiment, inaccurate pathological mosaic images from 20 groups were revised rapidly and accurately with error controlled within one pixel. It was proved that the approach is effective in revising the error matching in microscopic images mosaic. Moreover, it is easy to operate and effective for more accurate image stitching.
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Статья научная
In this paper, we propose two algorithms based on the popular Bit Plane Splicing Least Significant Bit (LSB) Technique for secret data hiding inside images. One major disadvantage of Bit Plane Splicing LSB technique is its low hiding capacity which results in severe degradation of the cover image upon hiding large amount of data. The proposed algorithms overcome this issue by imposing hiding rules based on the intensity level of pixels. In addition the method for data hiding is done in a non sequential manner using linear congruent random number generators. Experiment results show that the proposed techniques called Optimum Intensity Based Distributed Hiding (OIBDH) technique and Linear Congruent Optimum Intensity Based Distributed Hiding with Key (LC-OIBDH-k) outperforms Bit Plane Splicing LSB technique as they have better hiding capacity with less degradation in the cover image. Furthermore, the proposed algorithms are tested using absolute entropy curves and results show that our proposed techniques have lower absolute entropy difference compared to Bit Plane Splicing LSB technique in all the tested images and for different secret data sizes.
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Improved Cryptanalysis of CMC Chaotic Image Encryption Scheme
Статья научная
Recently, chaos has attracted much attention in the field of cryptography. To study the security with a known image of a symmetric image encryption scheme, the attack algorithm of equivalent key is given. We give the known image attacks under different other conditions to obtain the equivalent key. The concrete step and complexity of the attack algorithm is given. So the symmetric image encryption scheme based on 3D chaotic cat maps is not secure.
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Статья научная
The purpose of speech emotion recognition system is to classify speaker's utterances into different emotional states such as disgust, boredom, sadness, neutral and happiness. Speech features that are commonly used in speech emotion recognition (SER) rely on global utterance level prosodic features. In our work, we evaluate the impact of frame-level feature extraction. The speech samples are from Berlin emotional database and the features extracted from these utterances are energy, different variant of mel frequency cepstrum coefficients (MFCC), velocity and acceleration features. The idea is to explore the successful approach in the literature of speaker recognition GMM-UBM to handle with emotion identification tasks. In addition, we propose a classification scheme for the labeling of emotions on a continuous dimensional-based approach.
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Improved Parallel Lane Detection Using Modified Additive Hough Transform
Статья научная
Lane detection has recognition in real time vehicular ad-hoc system. That study work concentrate on giving greater efficiency in lane detection by utilizing the additive Hough transform to identify the curve lanes and convert into data parallelism in order to improve the speed of the proposed technique by using fork and join process. To accomplish performance evaluation various metrics is likely to be considered. The performance of lane detection algorithms is generally evaluated in terms of algorithm results and parallel results. Algorithm results is evaluated in terms of accuracy, error rate, execution time ,overhead and parallel results is evaluated in terms of speed, efficiency etc. To complete performance comparison the result of proposed algorithm is going to be compared with existing lane detection algorithms. Intelligent transportation systems are available these days for increasing the safety of the vehicles and reduce incident ratio. A new technique which uses modified additive hough transform is used to reduce the limitations of existing technique. The proposed algorithm has been designed and implemented in MATLAB.
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Improved Qrs Detector Using Parallel based Hybrid Mamemi Filter
Статья научная
QRS detection is becoming more popular in detecting the heart beat rate. The improvement is done by using the new filter. The data and control parallelism is used in order to improve the execution time and speed of the parallel based hybrid MAMEMI filter technique This research work focus on providing better performance in heart beat detection algorithm by using parallel hybrid filter.An enhanced algorithm has been proposed to enhance the performance of QRS detection. Different parameters are used for the performance analysis. Accuracy,F_Measure, and Detection_Error_rate are the parameters which are used to evaluate the performance of heart beat algorithm. The results of proposed algorithm are compared with existing heart beat detection algorithm for performance comparison. On the other hand the performance of the proposed method is also improved using parallelism. Parallel proposed method shows better results than Sequential proposed method. The Mean improvement in execution time is 0.80.
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Improved USCT of paired bones using wavelet-based image processing
Статья научная
Computed ultrasonic bone tomography (USCT) is a non-invasive and non-ionizing technique, which ensures the protection of child being against x-rays. The main objective of this article is to use an image processing algorithm to improve the signal-to-noise ratio of ultrasonic computed tomography (USCT) of children bones for automatic detection of osteopathologies. For this fact, we construct an application of image processing with Microsoft Foundation Class Library (FMC) integrated in visual Studio using Haar wavelet algorithm to detect edges. Different methods of image processing for automatic detection are used. Hence, we make accessible the detection of distance between bones due to the application of wavelet transform. As a result, the quality of USCT image was improved and the detection of child osteopathologies became accessible.
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Статья научная
Diabetic retinopathy is a severe and widely spread eye disease. Early diagnosis and timely treatment of these clinical signs such as hard exudates could efficiently prevent blindness. The presence of exudates within the macular region is a main hallmark of diabetic macular edema and allows its detection with high sensitivity. In this paper, we combine the k-means clustering algorithm and mathematical morphology to detect hard exudates (HEs) in retinal images of several diabetic patients. This method is tested on a set of 50 ophthalmologic images with variable brightness, color, and forms of HEs. The algorithm obtained a sensitivity of 95.92%, predictive value of 92.28% and accuracy of 99.70% using a lesion-based criterion.
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Статья научная
This paper performs three different contrast testing methods, namely contrast stretching, histogram equalization, and CLAHE using a median filter. Poor quality images will be corrected and performed with a median filter removal filter. STARE dataset images that use images with different contrast values for each image. For this reason, evaluating the results of the three parameters tested are; MSE, PSNR, and SSIM. With the gray level scale image and contrast stretching which stretches the pixel value by stretching the stretchlim technique with the MSE result are 9.15, PSNR is 42.14 dB, and SSIM is 0.88. And the HE method and median filter with the results of the average value of MSE is 18.67, PSNR is 41.33 dB, and SSIM is 0.77. Whereas for CLAHE and median filters the average yield of MSE is 28.42, PSNR is 35.30 dB, and SSIM is 0.86. From the test results, it can be seen that the proposed method has MSE and PSNR values as well as SSIM values.
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Статья научная
Face recognition is one of the most commonly used biometric features in the identification of people. In this article, a novel facial image recognition architecture is proposed with a novel image descriptor which is called as fully center symmetric dual cross pattern (FCSDCP) The proposed architecture consists of preprocessing, feature extraction and classification phases. In the preprocessing phase, discrete wavelet transform (DWT) and Neutrosophy are used together to calculate coefficients of the face images. The proposed FCSDCP extracts features. LDA, QDA, SVM and KNN are utilized as classifiers. 4 datasets were chosen to obtain experiments and the results of the proposed method were compared to other state of art image descriptor based methods and the results clearly shows that the proposed method is a successful method for face classification.
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Improving the MRI Tumor Segmentation Process Using Appropriate Image Processing Techniques
Статья научная
Segmenting tumor from MRI images is an essential but time consuming manual duty. Performing an automatic segmentation is a defying task since different forms of tumor tissue exist for diverse patients and in many cases the tumor is similar to the normal tissue. Various studies proposed earlier to handle the issue of precisely segmenting the tumor but they discard the degradations and their effect to the precision of the segmentation. This article provides a more precise segmentation process through the use of appropriate pre-processing algorithms. The authors studied many enhancement and restoration algorithms and selected the NL-means, Laplacian filter and histogram equalization to be used as preprocessing techniques. Experimental results showed that using a suitable preprocessing scheme would produce a better segmentation process.
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Статья научная
The security of digital image watermarking is improved by scrambling the watermark using different chaotic maps or cellular automata in such a way that an unauthorized person can't recover the watermark without the secret keys. In this proposed scheme three secret keys are used in which one key is used to make the watermark chaotic and other two keys are used for scrambling the cover image. In this scheme the cover image is scrambled by using the game of life cellular automation and the watermark is made chaotic by performing the X-OR operation between the binary watermark and logistic map. Although it increases the computational complexities, but the security of watermarking is improved by involving three secret keys. In addition, for ensuring imperceptibility and making the watermarking robust, a mask of size 3×3 is run over the scrambled cover image in which one bit of chaotic watermark is embedded in 3×3 block of cover image by modifying one of the neighbor pixels. Then the scrambled modified cover image is descrambled using game of life cellular automation for obtaining watermarked image. This proposed combined chaotic and cellular automata based watermarking scheme is compared with existing chaotic based watermarking schemes and gives satisfactory values of Peak Signal to Noise (PSNR), Mean Squared Error (MSE) and Normalized Correlation (NC).
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Improving the sharpness of digital image using an amended unsharp mask filter
Статья научная
Many of the existing imaging systems produce images with blurry appearance due to various existing limitations. Thus, a proper sharpening technique is usually used to increase the acutance of the obtained images. The unsharp mask filter is a well-known sharpening technique that is used to recover acceptable quality results from their blurry counterparts. However, this filter often introduces an overshoot effect, which is an undesirable effect that makes the recovered edges appear with visible white shades around them. In this article, an amended unsharp mask filter is developed to sharpen different digital images without introducing the overshoot effect. In the developed filter, the image is smoothed by using the traditional bilateral filter and then blurred using a modified Butterworth filter instead of blurring it with a Gaussian low-pass filter only as in the traditional unsharp mask filter. Using this approach allowed to eliminate the overshoot effect and to recover better quality results. The proposed filter is assessed by using two modern image quality assessment metrics, real and synthetic-blurred images, and is compared with three renowned image sharpening techniques. Various experiments and comparisons showed that the proposed filter produced promising results with both real and synthetic-blurred images.
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Improvised Salient Object Detection and Manipulation
Статья научная
In case of salient subject recognition, computer algorithms have been heavily relied on scanning of images from top-left to bottom-right systematically and apply brute-force when attempting to locate objects of interest. Thus, the process turns out to be quite time consuming. Here a novel approach and a simple solution to the above problem is discussed. In this paper, we implement an approach to object manipulation and detection through segmentation map, which would help to de-saturate or, in other words, wash out the background of the image. Evaluation for the performance is carried out using the Jaccard index against the well-known Ground-truth target box technique.
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