Essays about: "Contrast Limited Adaptive Histogram Equalization."

Showing result 1 - 5 of 6 essays containing the words Contrast Limited Adaptive Histogram Equalization..

1. 1. Image enhancement effect on the performance of convolutional neural networks

   University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Author : Xiaoran Chen; [2019]
   Keywords : Image Enhancement; Convolutional Neural Networks; Deep Learning; Transfer Learning;

   Abstract : Context. Image enhancement algorithms can be used to enhance the visual effects of images in the field of human vision. So can image enhancement algorithms be used in the field of computer vision? The convolutional neural network, as the most powerful image classifier at present, has excellent performance in the field of image recognition. READ MORE

3. 2. Image Enhancement & Automatic Detection of Exudates in Diabetic Retinopathy

   University essay from Blekinge Tekniska Högskola/Institutionen för tillämpad signalbehandling

   Author : Vivek Mallampati; [2019]
   Keywords : Exudates; Diabetic Retinopathy; Mahalanobis Distance; Histogram Equalization; Contrast Limited Adaptive Histogram Equalization.;

   Abstract : Diabetic retinopathy (DR) is becoming a global health concern, which causes the loss of vision of most patients with the disease. Due to the vast prevalence of the disease, the automated detection of the DR is needed for quick diagnoses where the progress of the disease is monitored by detection of exudates changes and their classifications in the fundus retina images. READ MORE

4. 3. An evaluation of image preprocessing for classification of Malaria parasitization using convolutional neural networks

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Erik Engelhardt; Simon Jäger; [2019]
   Keywords : Deep Learning; Convolutional Neural Network; Malaria; Image Recognition; Preprocessing; Computer Aided Diagnosis; Grayscale; Normalization; Histogram Equalization; CLAHE.; Deep Learning; Convolutional Neural Network; Malaria; Image Recognition; Preprocessing; Computer Aided Diagnosis; Grayscale; Normalization; Histogram Equalization; CLAHE.;

   Abstract : In this study, the impact of multiple image preprocessing methods on Convolutional Neural Networks (CNN) was studied. Metrics such as accuracy, precision, recall and F1-score (Hossin et al. 2011) were evaluated. Specifically, this study is geared towards malaria classification using the data set made available by the U. READ MORE

5. 4. Classification of skin pixels in images : Using feature recognition and threshold segmentation

   University essay from Umeå universitet/Institutionen för datavetenskap

   Author : Emil Samuelsson; [2018]
   Keywords : ;

   Abstract : The purpose of this report is to investigate and answer the research question: How can current skin segmentation thresholding methods be improved in terms of precision, accuracy, and efficiency by using feature recognition, pre- and post-processing? In this work, a novel algorithm is presented for classification of skin pixels in images. Different pre-processing methods were evaluated to improve the overall performance of the algorithm. READ MORE

6. 5. GPU-Accelerated Frame Pre-Processing for Use in Low Latency Computer Vision Applications

   University essay from Linköpings universitet/Informationskodning

   Author : Jonas Tarassu; [2017]
   Keywords : GPU; CUDA; OpenCL; CLAHE; RDC;

   Abstract : The attention for low latency computer vision and video processing applications are growing for every year, not least the VR and AR applications. In this thesis the Contrast Limited Adaptive Histogram Equalization (CLAHE) and Radial Dis- tortion algorithms are implemented using both CUDA and OpenCL to determine whether these type of algorithms are suitable for implementations aimed to run at GPUs when low latency is of utmost importance. READ MORE