- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 IEEE 3rd International Conference on Integrated Circuits and Microsystems (ICICM) - Shanghai, China (2018.11.24-2018.11.26)] 2018 IEEE 3rd International Conference on Integrated Circuits and Microsystems (ICICM) - Image Preprocessing of Iris Recognition
摘要： The aim of this paper is to propose the methods for image preprocessing of image enhancement and boundary detection. Iris recognition has been widely considered as one of the most dependable identification method. However, the iris systems are still not widespread due to many factors, for example, the production cost, the processing time and the recognition rate. The problems of production cost and the processing time will be resolved with the development of integrate circuit technology. The problem of recognition rate mentioned here is not about the iris itself, but the acquisition of the effective image of the iris. The quality of the iris image has become the key point of the current iris system. The preprocessing of iris recognition involves hardware and software design of the system and in this paper both of the designs are discussed.
关键词： Hough transform,iris recognition,image preprocessing,histogram equalization
更新于2025-09-23 15:22:29
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Color Image Enhancement Method with Variable Emphasis Degree
摘要： In this paper, we propose a new enhancement method for color images. In color image processing, hue preserving is required. The proposed method is performed into HSI color space whose gamut is same as RGB color space. The differential gray-level histogram equalization (DHE) is effective for gray scale images. The proposed method is an extension version of the DHE for color images, and furthermore, the enhancement degree is variable by introducing two parameters. Since our processing method is applied to not only intensity but also saturation, the contrast and the colorfulness of the output image can be varied. It is an important issue how to determine the two parameters. Thus, we give the guideline for how to decide the two parameters. By using the guideline, users can easily obtain their own enhancement images.
关键词： contrast,color image enhancement,differential gray-level histogram equalization,intensity saturation,colorfulness
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - 2D Multi-Band PCA and its Application for Ear Recognition
摘要： Principal Component Analysis (PCA) has been successfully used for many application including ear recognition. However, its performance is limited due to its significant data dependency. This paper presents a two dimensional multi-band PCA (2D-MBPCA) method, which has shown a significantly higher performance to that of the PCA. The proposed method divided the input gray image into a number of images, based on the intensity of its pixels using either a dynamic or predefined equal range of threshold values. PCA is then applied on the resulting set of images to extract their features. The resulting features are used to find the best match. The application of the proposed 2D-MBPCA for ear recognition using two benchmark ear image datasets, shows the merit of the proposed technique to that of the standard PCA.
关键词： ear recognition,histogram equalization,PCA
更新于2025-09-23 15:22:29
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Performance Evaluation of Image Enhancement Techniques
摘要： Color Image enhancement is a process in which the perceptual information of an image is improved to obtain more information and details contained in the image. It improves the subjective quality of an image by working with original data. This paper focuses on evaluating the performance of various image enhancement techniques. These techniques are either based on histogram modification or are based on fuzzy logic. The techniques are compared using two quantitative measures namely; Contrast Improvement index (CII) and Tenengrad measure. The results have shown that Lab and edge preservation based fuzzy image enhancement (LEFM) yields the best results.
关键词： edge preserving smoothing,Lab color space,fuzzy logic,Color image,Histogram equalization
更新于2025-09-23 15:21:01
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[IEEE 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI, USA (2018.7.18-2018.7.21)] 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Introducing a Novel Layer in Convolutional Neural Network for Automatic Identification of Diabetic Retinopathy
摘要： Convolutional neural networks have been widely used for identifying diabetic retinopathy on color fundus images. For such application, we proposed a novel framework for the convolutional neural network architecture by embedding a preprocessing layer followed by the first convolutional layer to increase the performance of the convolutional neural network classifier. Two image enhancement techniques i.e. 1- Contrast Enhancement 2- Contrast-limited adaptive histogram equalization were separately embedded in the proposed layer and the results were compared. For identification of exudates, hemorrhages and microaneurysms, the proposed framework achieved the total accuracy of 87.6%, and 83.9% for the contrast enhancement and contrast-limited adaptive histogram equalization layers, respectively. However, the total accuracy of the convolutional neural network alone without the prreprocessing layer was found to be 81.4%. Consequently, the new convolutional neural network architecture with the proposed preprocessing layer improved the performance of convolutional neural network.
关键词： contrast-limited adaptive histogram equalization,contrast enhancement,preprocessing layer,diabetic retinopathy,Convolutional neural networks,image enhancement
更新于2025-09-10 09:29:36
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Improved Image Fusion of Colored and Grayscale Medical Images Based on Intuitionistic Fuzzy Sets
摘要： Image fusion is the process of combining the properties of two images into one single image that will show the features of both the images. There are various methods available in the literature to fuse the images. In this paper, an intuitionistic fuzzy logic-based image fusion approach has been implemented for medical images that firstly suppresses the noise and enhances the input images, and merges them efficiently in Hue-Saturation-Intensity domain. Here, enhancement is included because these input images are not always well contrasted and may contain some noise due to the inherent properties of the modalities used for capturing the images. The intuitionistic fuzzy sets are incorporated to handle uncertainties that are often due to vagueness and ambiguity. The results certify that this method significantly improves the output fused image than the image obtained by existing technique both visually and metrically.
关键词： fuzzy histogram equalization,Image fusion,contrast enhancement,intuitionistic fuzzy sets
更新于2025-09-10 09:29:36
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[IEEE 2018 2nd International Conference on Engineering Innovation (ICEI) - Bangkok (2018.7.5-2018.7.6)] 2018 2nd International Conference on Engineering Innovation (ICEI) - Diabetic retinopathy fundus image classification using discrete wavelet transform
摘要： Diabetes is an incurable disease which erodes away body slowly, this disease in becoming common and becoming a cause of social distress. The only solution to this problem is early detection of disease and take precautionary measure to keep its effects to minimum. Since it affects various parts of body, the affected organ also includes eye which is very sensitive to any kind of distress. Diabetic Retinopathy effects of diabetes on eye retina, which includes rupturing of retina blood vessels and abnormal growth of blood vessels in retina, which ultimately causes blindness. Diabetic Retinopathy can be identified by examining the retinoscopy images. In this paper, retinoscopy images were processed using wavelet transform. Wavelet coefficients extracted from the images were obtained to identify Diabetic Retinopathy. KNN and SVM were used to classify the retinoscopy images. This papers have shown remarkable improvement as compared to previous studies, with KNN at 98.16 % accuracy and SVM at 97.85 % accuracy.
关键词： sensitivity,specificity,Discrete Wavelet Transform (DWT),accuracy,KNN,Diabetic Retinopathy (DR),histogram equalization,SVM
更新于2025-09-10 09:29:36
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Comparative study of image enhancement techniques using histogram equalization on degraded images
摘要： Image Enhancement technique plays a vital role in digital image processing for making an image to be useful for various applications. This technique is used to improve the quality of degraded images. Usually, the degradation is not evenly spread throughout the image, but most of the time it varies from region to region. Our aim is to first identify the region where enhancement is required and improve that region without disturbing its neighbourhood which does not require any improvement.
关键词： Image Histogram,Contrast Limited Adaptive Histogram Equalization (CLAHE),Image Enhancement,Histogram Equalization (HE)
更新于2025-09-09 09:28:46
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[IEEE 2018 International Conference on Soft-computing and Network Security (ICSNS) - Coimbatore, India (2018.2.14-2018.2.16)] 2018 International Conference on Soft-computing and Network Security (ICSNS) - Improving Optical Braille Recognition in Pre-processing Stage
摘要： Braille documents are captured and processed and converted into natural text using Optical Braille Recognition (OBR) system. Braille data or information which is embossed on Braille plate is most commonly captured by mobile camera or scanner into Braille image is the input to OBR. Preprocessing is the first stage performed by OBR system. The Noise introduced while Image captured using camera, mobile or scanners involve irregular lightness, low quality image due to less pixel camera, impulse noise, diverse gray-level values, angled or slanted image captured as a result of human error, deformation or warp of image document, deprived or disabled dots, appearance of unwanted dots, irregular gap between adjacent dots that represent a character. Various image enhancement techniques are applied in preprocessing stage to abolished or reduce such impulse noises. The main mission of the paper is to understand and apply a proportional learning of diverse preprocessing techniques on the Braille image and identify the best method to improve quality of Braille image.
关键词： Braille,Box filter,preprocessing,Spatial filter,Gaussian filter,Smoothing,Histogram Equalization,OCR,OBR
更新于2025-09-09 09:28:46
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A software supported image enhancement approach based on DCT and quantile dependent enhancement with a total control on enhancement level
摘要： In many computer vision applications like medical imaging, pattern recognition etc., image enhancement is an important pre-processing requirement which is used to improve the efficiency of an application. A significantly large literature is available on image enhancement; unfortunately, most of these schemes have certain shortcomings for e.g. the lack of control over the contrast starching, noise enhancement and ‘mean-shift’ problem etc. To deal with the aforementioned problems, this study suggests an efficient method which is based on discrete cosine transformation (DCT) and quantile dependent sub-division of the histogram of given input image. In the proposed method, we apply DCT on the input image to get low-frequency component (LFC) and then use the quantile-based sub-division on the histogram of LFC. Finally, histogram equalization is performed on all these sub-histograms separately. The main advantage of quantile-based segmentation is that here entire intensity spectrum participates in the enhancement process, which provides a total control over the enhancement level. In the proposed method the high-frequency component remains untouched and hence the structural information of the input image and the noise in the input image remains unaffected by the image enhancement process.
关键词： Linearly quantile separated histogram equalization,Contrast enhancement,Mean-shift problem,Discrete cosine transform,Greyscale images
更新于2025-09-04 15:30:14