image processing Archives — MATLAB Number ONE https://matlab1.com/category/image-processing/ MATLAB Simulink | Tutorial | Code | Project Thu, 28 Jan 2021 15:29:25 +0000 en-GB hourly 1 https://matlab1.com/wp-content/uploads/2018/08/icon1-100x100.png image processing Archives — MATLAB Number ONE https://matlab1.com/category/image-processing/ 32 32 Cooperation in Perception in Autonomous driving https://matlab1.com/cooperation-in-perception-in-autonomous-driving/ https://matlab1.com/cooperation-in-perception-in-autonomous-driving/#respond Thu, 28 Jan 2021 15:29:25 +0000 https://matlab1.com/?p=7185 Cooperation Autonomous driving is an extremely difficult task requiring absolute reliability under a great variety of situations. Currently, it is almost impossible for a single sensor to handle the complexity due to limited perspective and intrinsic weakness such as a camera’s bad adaptability to complicated light conditions. Researchers therefore propose collaborative methods to stretch the […]

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]]> https://matlab1.com/cooperation-in-perception-in-autonomous-driving/feed/ 0 Perception in Self-driving https://matlab1.com/perception-in-self-driving/ https://matlab1.com/perception-in-self-driving/#respond Wed, 27 Jan 2021 17:41:34 +0000 https://matlab1.com/?p=7139 Sensors Various types of sensors are used for perception in the self-driving industry. Most current solutions rely on either a camera or LIDAR as the main sensor. A camera captures reflections of light passively and stores data as 2D images. In contrast, LIDAR actively emits point laser beams and measures the distance to the point […]

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]]> https://matlab1.com/perception-in-self-driving/feed/ 0 Python projektet https://matlab1.com/python-projektet/ https://matlab1.com/python-projektet/#respond Sat, 16 Jun 2018 04:38:59 +0000 https://matlab1.com/?p=5631 Jag är en pythonprogrammerare. Jag har fyra års erfarenhet av python. Jag är redo att acceptera Python-projektet.   Keras, TensorFlow, Scipy, Numpy, Konstgjort neuralt nätverk i Python, Bildbehandling i Python, OpenCV, Pybrain, Matplotlib, Scikit-Learn , Pandas Djupt lärande i Python, Maskinlärning i Python Kontakt: matlab120 [[attt]] gmail [[[dot]] com Vänligen skicka e-post på engelska.   […]

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]]> https://matlab1.com/python-projektet/feed/ 0 Autoencoders of raw images in TensorFlow https://matlab1.com/autoencoders-of-raw-images-in-tensorflow/ https://matlab1.com/autoencoders-of-raw-images-in-tensorflow/#respond Sun, 10 Jun 2018 10:54:52 +0000 https://matlab1.com/?p=5587 An autoencoder is an unsupervised algorithm for generating efficient encodings. The input layer and the target output is typically the same. The layers between decrease and increase in the following fashion:  The bottleneck layer is the middle layer with a reduced dimension. The left side of the bottleneck layer is called encoder and the right […]

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]]> https://matlab1.com/autoencoders-of-raw-images-in-tensorflow/feed/ 0 Matching faster using approximate nearest neighbour in TensorFlow https://matlab1.com/matching-faster-using-approximate-nearest-neighbour-in-tensorflow/ https://matlab1.com/matching-faster-using-approximate-nearest-neighbour-in-tensorflow/#respond Sun, 10 Jun 2018 10:51:49 +0000 https://matlab1.com/?p=5583 Approximate nearest neighbour oh yeah (ANNOY) is a method for faster nearest neighbour search. ANNOY builds trees by random projections. The tree structure makes it easier to find the closest matches. You can create an ANNOYIndex for faster retrieval as shown here: def create_annoy(target_features): t = AnnoyIndex(layer_dimension) for idx, target_feature in enumerate(target_features): t.add_item(idx, target_feature) t.build(10) […]

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]]> https://matlab1.com/matching-faster-using-approximate-nearest-neighbour-in-tensorflow/feed/ 0 Efficient retrieval https://matlab1.com/efficient-retrieval/ https://matlab1.com/efficient-retrieval/#respond Sun, 10 Jun 2018 10:50:41 +0000 https://matlab1.com/?p=5580 The retrieval can be slow because it’s a brute-force method. Matching can be made faster using approximate nearest neighbor. The curse of dimensionality also kicks in, as shown in the following figure: With every increasing dimension, complexity increases as the complexity from two dimensions to three dimensions. The computation of the distance also becomes slower. […]

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]]> https://matlab1.com/efficient-retrieval/feed/ 0 Computing similarity between query image and target database https://matlab1.com/computing-similarity-between-query-image-and-target-database/ https://matlab1.com/computing-similarity-between-query-image-and-target-database/#respond Sun, 10 Jun 2018 10:49:22 +0000 https://matlab1.com/?p=5578 NumPy’s linalg.norm is useful for computing the Euclidean distance. The similarity between the query image and target database can be computed between the images by calculating the Euclidean distances between the features as shown here: dist = np.linalg.norm(np.asarray(query_feature) - np.asarray(target_feature)) print(dist) Running this command should print the following: <strong>16.9965</strong> This is the metric that can be […]

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]]> https://matlab1.com/computing-similarity-between-query-image-and-target-database/feed/ 0 Building the retrieval pipeline https://matlab1.com/building-the-retrieval-pipeline/ https://matlab1.com/building-the-retrieval-pipeline/#respond Sun, 10 Jun 2018 10:40:34 +0000 https://matlab1.com/?p=5573 The sequence of steps to get the best matches from target images for a query image is called the retrieval pipeline. The retrieval pipeline has multiple steps or components. The features of the image database have to be extracted offline and stored in a database. For every query image, the feature has to be extracted […]

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]]> https://matlab1.com/building-the-retrieval-pipeline/feed/ 0 Content-based image retrieval https://matlab1.com/content-based-image-retrieval/ https://matlab1.com/content-based-image-retrieval/#respond Sun, 10 Jun 2018 10:38:35 +0000 https://matlab1.com/?p=5571 The technique of Content-based Image Retrieval (CBIR) takes a query image as the input and ranks images from a database of target images, producing the output. CBIR is an image to image search engine with a specific goal. A database of target images is required for retrieval. The target images with the minimum distance from the query […]

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]]> https://matlab1.com/content-based-image-retrieval/feed/ 0 Sinc interpolation on input waveforms https://matlab1.com/sinc-interpolation-on-input-waveforms/ https://matlab1.com/sinc-interpolation-on-input-waveforms/#respond Thu, 15 Mar 2018 13:28:46 +0000 https://matlab1.com/?p=4378 function [yi, ypi] = sincdint(x, y, xi, c) % SINCDINT 1-D piecewise discrete sinc interpolation % SINCDINT(X,Y,XI,C) interpolates to find YI, the values of the % underlying function Y at the points in the array XI, using % piecewise discrete sinc interpolation. X and Y must be vectors % of length N. % % C […]

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