title: Advantages of 3D time-of-flight range imaging cameras in machine vision applications

authors: Dorrington, Adrian A.

subjects: range imaging

abstract: Machine vision using image processing of traditional intensity images is in wide spread use. In many situations environmental conditions or object colours or shades cannot be controlled, leading to difficulties in correctly processing the images and requiring complicated processing algorithms. Many of these complications can be avoided by using range image data, instead of intensity data. This is because range image data represents the physical properties of object location and shape, practically independently of object colour or shading. The advantages of range image processing are presented, along with three example applications that show how robust machine vision results can be obtained with relatively simple range image processing in real-time applications.

text: Advantages of 3D time-of-flight range imaging cameras in machine vision applications Machine vision using image processing of traditional intensity images is in wide spread use. In many situations environmental conditions or object colours or shades cannot be controlled, leading to difficulties in correctly processing the images and requiring complicated processing algorithms. Many of these complications can be avoided by using range image data, instead of intensity data. This is because range image data represents the physical properties of object location and shape, practically independently of object colour or shading. The advantages of range image processing are presented, along with three example applications that show how robust machine vision results can be obtained with relatively simple range image processing in real-time applications.

year: 2009

title: Compression-based template matching

authors: Inglis, Stuart J.

subjects: Machine learning

abstract: Textual image compression is a method of both lossy and lossless image compression that is particularly effective for images containing repeated sub-images, notably pages of text (Mohiuddin et al., 1984; Witten et al., 1992). The process comprises three main steps:
• Extracting all the characters from an image;
• Building a library that contains one representative for each character class;
• Compressing the image with respect to the library.

text: Compression-based template matching Textual image compression is a method of both lossy and lossless image compression that is particularly effective for images containing repeated sub-images, notably pages of text (Mohiuddin et al., 1984; Witten et al., 1992). The process comprises three main steps:
• Extracting all the characters from an image;
• Building a library that contains one representative for each character class;
• Compressing the image with respect to the library.

year: 1993

title: He pakiriha

authors: Temara, Pou

subjects: Tikanga

abstract: Kua tae ki te wā hai kōrero i ētahi tikanga marae, ētahi tikanga kawa e kawa ana ki tā te mātanga titiro. Tērā ētahi tikanga e whakamahia ana e ngā kaumātua o nāianei e uru atu ana ki te pae o rorirori, ka mutu, e ai ki tā ngā kaumātua nei, ko te mutunga mai o te tika ā rātau i whakatau ai. Nā hei whakarāpopoto i te whakaaro whānui, i ētahi wā kāore ko te mea e tika ana ki ō tātau whakaaro te huarahi pai. Ko tā te tikanga he kimi i te huarahi e tika ana, kia kore ai e whara ngā whakaaro o te tangata. Ko te tikanga ehara i te mea i whakairotia ki te kōhatu, engari e taea ana te neke i ngā pae o te tikanga kia pai ai te whakahaere a te tangata i āna mahi, kia tau ai te rangimārie, kia mau tonu ai te mana o te tangata. E whakapae ana ahau e kūmea ana e ētahi kaumātua ētahi tikanga kia hāngai ki tā rātau i whakaaro ai kai te tika, kai te hē rānei. Mā ētahi tauira e mārama ai te kaipānui ki te kaupapa me te whakaaro o te kaituhi.

text: He pakiriha Kua tae ki te wā hai kōrero i ētahi tikanga marae, ētahi tikanga kawa e kawa ana ki tā te mātanga titiro. Tērā ētahi tikanga e whakamahia ana e ngā kaumātua o nāianei e uru atu ana ki te pae o rorirori, ka mutu, e ai ki tā ngā kaumātua nei, ko te mutunga mai o te tika ā rātau i whakatau ai. Nā hei whakarāpopoto i te whakaaro whānui, i ētahi wā kāore ko te mea e tika ana ki ō tātau whakaaro te huarahi pai. Ko tā te tikanga he kimi i te huarahi e tika ana, kia kore ai e whara ngā whakaaro o te tangata. Ko te tikanga ehara i te mea i whakairotia ki te kōhatu, engari e taea ana te neke i ngā pae o te tikanga kia pai ai te whakahaere a te tangata i āna mahi, kia tau ai te rangimārie, kia mau tonu ai te mana o te tangata. E whakapae ana ahau e kūmea ana e ētahi kaumātua ētahi tikanga kia hāngai ki tā rātau i whakaaro ai kai te tika, kai te hē rānei. Mā ētahi tauira e mārama ai te kaipānui ki te kaupapa me te whakaaro o te kaituhi.

year: 2017