Topic
Image conversion
About: Image conversion is a research topic. Over the lifetime, 2490 publications have been published within this topic receiving 19077 citations.
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Patent•
25 May 2001
TL;DR: In this paper, an R component, a G component and a B component in 8-bit each being components of a color image are divided into data each having a bit size in 3-bits, in 2-bits and in 1-bit respectively.
Abstract: PROBLEM TO BE SOLVED: To provide an image conversion method that can decode a color image in the case of converting a color image into the monochrome image. SOLUTION: An R component, a G component and a B component in 8-bit each being components of a color image are divided into data each having a bit size in 3-bits, in 3-bits and in 2-bits respectively (S101). Then each bit (digit) value of the divided data is extracted (S102), the extracted values are arranged in a prescribed sequence such as G8, R8, B8, G7, R7, B7, G6, R6 (S103), and the monochrome image is displayed in data in 8-bits arranged in this way (S104).
1 citations
Patent•
26 Nov 2019
TL;DR: In this paper, a multielement photoconverter generates an electrical signal of image frames in three spectral bands, each of which is simultaneously passed through a Gauss filter, multiplied by a correction coefficient, and the obtained signals are normalized to a full span, inter-frame differences of the consecutively processed blue and red frames are accumulated and compared to the preset thresholds.
Abstract: FIELD: image processing means.SUBSTANCE: invention relates to conversion of object images observed by television systems, in particular smoke and flame images. Multielement photoconverter generates an electrical signal of image frames in three spectral bands, each of which is simultaneously passed through a Gauss filter, multiplied by a correction coefficient, then, to obtain a smoke signal from the blue frame signal, subtracting filtered red and green frames signals, to obtain flame signals from the red frame signal, blue and green frame signals are subtracted, the obtained signals are normalized to a full span, inter-frame differences of the consecutively processed blue and red frames are accumulated and compared to the preset thresholds.EFFECT: reduced effect of dynamically changing background, simultaneous generation of smoke and flame signals.1 cl, 1 dwg
1 citations
Patent•
25 Jul 2012
TL;DR: Wang et al. as discussed by the authors proposed a gastric ulcer model evaluation method based on grey-scale image analysis, which comprises three steps, which are image collection, image conversion, and data processing and ulcer index calculation.
Abstract: The invention discloses a gastric ulcer model evaluation method based on grey-scale image analysis The method comprises three steps, which are image collection, image conversion, and data processing and ulcer index calculation In the image collection step, a sample is placed in a dark box with a fixed volume and a fixed light source; and color (RPG) images are collected by shooting by using image collection tools such as a digital camera In the image conversion step, analysis software such as ImageJ is adopted, and the collected color images are subject to grey-scale image conversion, gastric mucosa region image selection and pixel statistics, and gastric ulcer region image selection and pixel statistics In the data processing and ulcer index calculation step, in units of pixel points, the percentage of the area of the gastric ulcer region in the mucous membrane gross area is calculated, and is adopted as the ulcer index for evaluating the gastric ulcer model With the method, rat/mice experimental gastric ulcer models can be accurately evaluated The method is also suitable for other image analysis and statistics with images as targets
1 citations
Patent•
17 Oct 2003
TL;DR: In this article, the problem of detecting a deviation between an even number field and an odd number field in the case of converting an imaged image by an interlaced camera and comprising the even number fields and the odd number filed was addressed.
Abstract: PROBLEM TO BE SOLVED: To provide an image conversion method and an image conversion apparatus for preventing blurs in an image after converting an image consisting of an even number field image and an odd number field image SOLUTION: The image conversion method is characterized to include a step S002 of detecting a deviation between an even number field and an odd number field in the case of converting an imaged image by an interlaced camera and comprising the even number field and the odd number filed; a step S004 of converting the image on the basis of an interlaced image consisting of the even number field and the odd number field when a deviation (ΣΔI) between the fields is smaller than a prescribed value (Ith); and a step S005 of converting the image on the basis of either the even number field or the odd number filed when the deviation (ΣΔI) between the fields is greater than the prescribed value (Ith) COPYRIGHT: (C)2004,JPO
1 citations
Patent•
28 May 2015
TL;DR: In this article, the interpolation feature amount is generated on the basis of a distance on the feature amount space, where the distance is defined by a distance measure between a local feature amount corresponding to the learning image and the conversion image.
Abstract: PROBLEM TO BE SOLVED: To easily and quickly generate a lot of local feature amounts for learning.SOLUTION: An image conversion part 1 converts a learning image 101 to generate a conversion image. A feature amount obtaining part 2 obtains a local feature amount for each of a learning image and the conversion image. A feature amount position determination part 3 specifies local feature amounts whose positions on an image space are almost identical. Between a local feature amount corresponding to the learning image and a local feature amount corresponding to the conversion image, among local feature amounts thus specified, an interpolation feature amount generation part 4 generates an interpolation feature amount. Here, the interpolation feature amount is generated on the basis of a distance on the feature amount space. A learning data specification part 5 specifies a local feature amount for learning by using the interpolation feature amount.
1 citations