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Project Zone > Electronics > Image Processing

Lung Nodule Classification With Multilevel Patch-Based Context Analysis

Category : Image Processing


Sub Category : BIOMEDICAL


Project Code : IMP21


Project Desc : We propose a novel classification method for the four types of lung nodules, i.e., well-circumscribed, vascularized, juxta-pleural, and pleural-tail, in low dose computed tomography scans.

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An Automatic Graph-Based Approach for Artery/Vein

Category : Image Processing


Sub Category : BIOMEDICAL


Project Code : IMP22


Project Desc : The classification of retinal vessels into artery/vein (A/V) is an important phase for automating the detection of vascular changes, and for the calculation of characteristic signs associated with several systemic diseases such as diabetes, hypertension, and other cardiovascular conditions.

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On Scanning Linear Barcodes From Out-of-Focus Blurred Images: A Spatial Domain Dynamic Template Matching Approach

Category : Image Processing


Sub Category : RESTORATION


Project Code : IMP23


Project Desc : We present a novel linear barcode scanning system based on a dynamic template matching scheme. The proposed system works entirely in the spatial domain, and is capable of reading linear barcodes from low-resolution images containing severe OOF blur.

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Remote Sensing Image Segmentation by Combining Spectral and Texture Features

Category : Image Processing


Sub Category : SEGMENTATION


Project Code : IMP24


Project Desc : We present a new method for remote sensing image segmentation, which utilizes both spectral and texture information. Linear filters are used to provide enhanced spatial patterns. For each pixel location, we compute combined spectral and texture features using local spectral histograms, which concatenate local histograms of all input bands.

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Object-Oriented Shadow Detection and Removal From Urban High-Resolution Remote Sensing Images

Category : Image Processing


Sub Category : RESTORATION


Project Code : IMP25


Project Desc : Shadow features are taken into consideration during image segmentation, and then, according to the statistical features of the images, suspected shadows are extracted. Furthermore, some dark objects which could be mistaken for shadows are ruled out according to object properties and spatial relationship between objects.

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Fuzzy Clustering With a Modified MRF Energy Function for Change Detection in Synthetic Aperture Radar Images

Category : Image Processing


Sub Category : SEGMENTATION


Project Code : IMP26


Project Desc : This approach classifies changed and unchanged regions by fuzzy c-means (FCM) clustering with a novel Markov random field (MRF) energy function. In order to reduce the effect of speckle noise, a novel form of the MRF energy function with an additional term is established to modify the membership of each pixel.

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Measures of Effective Video Tracking

Category : Image Processing


Sub Category : SEGMENTATION


Project Code : IMP27


Project Desc : To evaluate multitarget video tracking results, one needs to quantify the accuracy of the estimated target-size and the Cardinality error as well as measure the frequency of occurrence of ID changes.

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